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Objective: Previous attempts to identify an 'obese eating style' have led to conflicting findings. This observational study compared the chewing features of overweight or obese young adults with those of normal range BMI. We hypothesised that chewing features are individual-specific and differ between participants of a normal BMI and high BMI., Methods: Fourteen overweight to obese participants (BMI≥25.0) were pairwise matched with 14 normal range BMI participants (18.50.05), whereas chewing power was significantly higher in high BMI participants (p<0.05). No other differences in chewing characteristics were found between BMI groups. Participants chewed at similar rate in the natural environment (pizza) and in the laboratory (rice) setting (p>0.05). Masticatory performance did not differ significantly (p>0.05) between the high (55.9%) and normal (52.4%) BMI groups., Conclusions: Within the limitations of the present study, chewing characteristics appear to be individual-specific with wide variability. Overweight participants chew at a similar rate to control participants, albeit slightly stronger. Our preliminary findings need to be replicated in larger samples., (Copyright © 2015. Published by Elsevier Inc.)

Background: Since 2000, the longitudinal Pacific Island Families study has measured the weight, height and body mass index (BMI) of 582 girls and 643 boys at 2, 4, 6 and 9 year data collection phases., Aim: To extend and record the age-related distribution of weight, height and BMI measures in Pacific children aged 2-10 years and to compare the distribution to population and clinical growth charts., Methods: Gender-specific age-related centile curves were derived using the LMS method for weight, height and BMI. The 50th centiles from the World Health Organisation growth reference for 2-5 year olds and the Centres for Disease Control (CDC) for 5-10 year olds were compared. Overweight and obesity were defined by the CDC BMI 85th and 95th centiles., Results: The proportion of children whose weight and height were above the reference 50th centile increased with age. At age 10, using CDC criteria, more than 50% of the children were classified as obese and 70% were overweight., Conclusions: These charts support the need to prioritize interventions for Pacific families to address childhood obesity. These centile curves could help assess the relative growth of Pacific children and identify children for further assessment and treatment.

Background/objectives: In 2002, the prevalence of overweight and obesity, defined by body mass index (BMI), was higher in New Zealand Māori (40%) and Pacific (60%) than in European (24%) children; however, this does not take into account interethnic differences in body composition. This study compared trajectories of anthropometric indices from 2004 to 2006 among 5- and 10-year-old Māori and European children., Subjects/methods: In 2004 and then in 2006, 1244 children (639 boys and 605 girls) aged 5 and 10 years had height, weight and fat-free mass (FFM) by bioimpedance measured to derive measures of fat mass (FM), percentage body fat (%BF), FM index (FMI, FM/height(2)), FFM index (FFMI, FFM/height(2)), and s.d. scores for BMI and %BF and BMI categories by International Obesity Task Force criteria., Results: Body composition and growth in Māori children is different from European children. Over 2 years, the BMI and %BF s.d. scores in both 5- and 10-year-old cohorts increased more in Māori children than in European children. The prevalence of overweight and obesity also increased within ethnicity and age group. The relative change of FMI and FFMI differed by age group, gender and ethnicity. In Māori girls, the magnitude of the changes between 10 and 12 years of age was most marked-the major contribution was from an increase in FMI. At 12 years, the mean %BF of Māori girls was 31.7% (95% confidence interval (CI): 30.1 and 33.3) compared with that of European girls (28.0%; 95% CI: 27.0 and 29.0)., Conclusions: FM and FFM measures provide a more appropriate understanding of growth and body composition change in children than BMI, and vary with gender and ethnicity. Thus, FMI and FFMI should be tracked and compared among populations.

Background: Pacific adults and children have very high rates of obesity., Objective: Body size at birth, 2- and 4 years for the whole cohort, compliant (not smoking and breastfed) and non-compliant children was compared to the 2006 World Health Organization (WHO) growth standard using z-scores., Design: Longitudinal data (n=659) from the 2000 Pacific Island family birth cohort study of weight at birth and weight and height at 2- and 4 years was analysed., Results: At birth the average child was 3.673+/-0.501 kg; z-score 0.605 units higher (P<0.000001) than the WHO standard. At 2- and 4 years, average z-scores for weight and body mass index (BMI) were significantly different from 0 (mean z-scores for weight +1.062 and +1.688, for BMI +1.701 and +1.969 respectively, P<0.000001). Mean height was significantly lower (P<0.000001) z-score=-0.232 at 2 years but higher (P<0.000001) at 4 years, z-score=+0.626. Over 4 years, the daily weight gain was 11.2 g day(-1) compared with 8.9 g day(-1) for the WHO child. Compliant (n=287) compared to non-compliant (n=372) weighed less and were slightly shorter at 2- and 4 years measurement points. Non-compliant children categorized as non-smoking (n=229) weighed more than smoking mothers' (n=143) children at birth, 2- and 4 years., Conclusion: Pacific children are born heavy, over 4 years increase in weight is faster and between 2- and 4 years increase in height is faster than the reference breastfed child, independent of pre- and postnatal factors. Smoking decreases the rate of weight gain and children who are not breastfed gain weight faster. Interventions to limit weight gain need to start with the family before conception.

Objective: To investigate body composition differences, especially the relationship between body mass index (BMI) and percent body fat (%BF), among five ethnic groups., Design: Cross-sectional., Subjects: Seven hundred and twenty-one apparently healthy women aged 18-60 years (BMI: 17.4-54.0 kg/m(2)) from South Africa (SA, 201 black, 94 European) and New Zealand (NZ, 173 European, 76 Maori, 84 Pacific, 93 Asian Indian)., Measurements: Anthropometry, including waist circumference, and total, central and peripheral body fat, bone mineral content and total appendicular skeletal muscle mass (ASMM) derived from dual X-ray absorptiometry., Results: Regression analysis determined that at a BMI of 30 kg/m(2), SA European women had a %BF of 39%, which corresponded to a BMI of 29 for SA black women. For a BMI of 30 kg/m(2) in NZ Europeans, equivalent to 43% body fat, the corresponding BMIs for NZ Maori, Pacific and Asian Indian women were 34, 36 and 26 kg/m(2), respectively. Central fat mass was lower in black SA than in European SA women (P<0.001). In NZ, Pacific women had the lowest central fat mass and highest ASMM, whereas Asian Indian women had the highest central fat mass, but lowest ASMM and bone mineral content., Conclusions: The relationship between %BF and BMI varies with ethnicity and may be due, in part, to differences in central fatness and muscularity. Use of universal BMI or waist cut-points may not be appropriate for comparison of obesity prevalence among differing ethnic groups, as they do not provide a consistent reflection of adiposity and fat distribution across ethnic groups.

In light of alarming rises in the prevalence of obesity worldwide, tackling the obesity 'epidemic' is now a national health priority in many countries. Increasingly, population measures that provide accurate estimates of body fatness are required to assist public health organisations in identifying at-risk groups and developing appropriate preventative strategies. Body mass index (BMI) remains the most cost-effective and practical tool in this regard. The World Health Organization (WHO) has issued universal BMI standards for defining 'overweight' and 'obesity' in adults (BMI > or =25 kg x m(-2), and > or =30 kg x m(-2), respectively) based on the risk of obesity-related disease in Europeans. Although widely used, there is mounting evidence suggesting that these standards are not appropriate for all populations. Research indicates that the associations between BMI, percent body fat (%BF), and health risks can vary across different ethnicities. Accordingly, ethnic-specific and country-specific BMI cut-offs for overweight and obesity may be necessary to attain valid prevalence estimates. In New Zealand, this area is largely unexplored in both young people and Asian populations. There is a need for large-scale longitudinal studies investigating the relationships between excessive body fatness and related health outcomes across all major ethnic groups in New Zealand.

Objective: To compare percentage body fat (%BF) for a given body mass index (BMI) among New Zealand European, Maori and Pacific Island children. To develop prediction equations based on bioimpedance measurements for the estimation of fat-free mass (FFM) appropriate to children in these three ethnic groups., Design: Cross-sectional study. Purposive sampling of schoolchildren aimed at recruiting three children of each sex and ethnicity for each year of age. Double cross-validation of FFM prediction equations developed by multiple regression., Setting: Local schools in Auckland., Subjects: Healthy European, Maori and Pacific Island children (n=172, 83 M, 89 F, mean age 9.4+/-2.8(s.d.), range 5-14 y)., Measurements: Height, weight, age, sex and ethnicity were recorded. FFM was derived from measurements of total body water by deuterium dilution and resistance and reactance were measured by bioimpedance analysis., Results: For fixed BMI, the Maori and Pacific Island girls averaged 3.7% lower %BF than European girls. For boys a similar relation was not found since BMI did not significantly influence %BF of European boys (P=0.18). Based on bioimpedance measurements a single prediction equation was developed for all children: FFM (kg)=0.622 height (cm)(2)/resistance+0.234 weight (kg)+1.166, R(2)=0.96, s.e.e.=2.44 kg. Ethnicity, age and sex were not significant predictors., Conclusions: A robust equation for estimation of FFM in New Zealand European, Maori and Pacific Island children in the 5-14 y age range that is more suitable than BMI for the determination of body fatness in field studies has been developed.

The prediction of total body fat from simple anthropometric measurements was examined in 42 white (New Zealand European and 40 Polynesian women aged 18-27 y. Percentage body fat (%BF) was determined from measurements of total body water (TBW) by 18O dilution. Mean (+/- SD) body mass index (BMI; in kg/m2) averaged 29.2 +/- 7.9 (range: 16.5-48.0) for the New Zealand European group and 31.2 +/- 7.9 (range: 19.8-51.8) for the Polynesian group, %BF calculated from TBW was similar in the two groups (40.5 +/- 9.9% for the New Zealand European compared with 39.1 +/- 7.5% for the Polynesian group). BMI was significantly correlated with height in the Polynesian group but not in the New Zealand European group. The relation between BMI and %BF was curvilinear for both groups. At a fixed %BF, BMI was higher in the Polynesian group than in the New Zealand European group. A BMI of 30 for the New Zealand European group corresponded to a BMI of 34 for the Polynesian group at an equivalent %BF (42%). Prediction equations for %BF developed from skinfold thicknesses or girth measurements were ethnicity dependent. We conclude that the BMI criterion for obesity in whites requires revision for use in Polynesians.

Hidden hunger is widespread in India. Individual dietary diversity score (IDDS) is a measure of the nutrient adequacy of the diet. The FAO has set guidelines for the measurement of dietary diversity: the IDDS and the minimum dietary diversity score for women (MDD-W) to assess nutritional deficiency, but validation against nutritional biomarkers is required. Using available data among rural youth (17 years) from the Pune Maternal Nutrition Study, the validity of DDS was assessed to measure deficiencies of vitamin B12, folate and Hb. Of the 355 boys and 305 girls, 19 % were classified as underweight, 57 % as vitamin B12 deficient (<150 pmol/l) and 22 % as anaemic (<120/130 g/l). Cereals, legumes and 'other-vegetables' were the most frequently consumed foods. More boys than girls consumed milk, flesh, eggs and micronutrient-dense foods. Median IDDS of 4 (interquartile range (IQR) 3–4) and MDD-W of 6 (IQR 5–7) were low. Youth with vitamin B12 deficiency had a higher likelihood of an IDDS ≤ 4 (1·89; 95 % CI 1·24, 2·87) or an MDD-W ≤ 5 (1·40; 95 % CI 1·02, 1·94). Youth with anaemia were more likely to have an IDDS ≤ 4 (1·76; 95 % CI 1·01, 3·14) adjusted for socio-economic scores, BMI, energy intake and sex. Folate deficiency was low (3 %) and was not associated with either score. Youth with lowest plasma vitamin B12 and Hb infrequently or never consumed dairy products/non-vegetarian foods. These rural Indian youth were underweight, had low DDS and consumed foods low in good-quality proteins and micronutrients. Associations of DDS with circulating micronutrients indicate that DDS is a valid measure to predict vitamin B12 deficiency and anaemia. [ABSTRACT FROM AUTHOR]

Energy intake (EI) and energy expenditure (EE) are relatively easy to measure accurately over short periods in a laboratory setting, but less so during a multi-day competition. Our goal was to measure EI and EE as accurately as possible during a 6-day, 10-stage cycling race. We prepared all meals and supplements, assessed EI (weighed diet-records) and macrontrient intake, total EE (doubly labelled water), resting metabolic rate (respiratory gas exchange), exercise EE (power meters), and body mass. Body composition was measured several days before and after racing (dual x-ray absorptiometry). Body mass remained stable over the course of the race. The mean EI (27.3±3.8 MJ/day) nearly matched EE (27.4±2.0 MJ/day). The majority (62%) of EE was exercise EE. Macronutrient intake was within or exceeded the recommendations. Lean body mass increased and fat mass decreased in most of our participants. Our study indicates that EI can match high EE with adequate macronutrient intake during multi-day cycle racing and may be facilitated by appropriate foods being available at appropriate times. This optimization of nutritional provision supports positive changes in body composition. [ABSTRACT FROM AUTHOR]

Background/Objectives:To investigate the relationships between body mass index (BMI), body fatness, ethnicity, age and blood lipids.Subjects/Method:In a subsample (N=643) of the 2002 New Zealand Child Nutrition Survey (N=3275, age 5–14 years) consisting Māori (89 boys, 69 girls), Pacific (154 boys, 194 girls) and European (71 boys, 66 girls) ethnic groups, fat-free mass (FFM) was determined by bioimpedance analysis. FFM index (FFMI, FFM/height2), fat mass index (FMI, fat mass/height2) and percentage body fat (%BF) were derived. Plasma total cholesterol and high-density lipoprotein (HDL) cholesterol were measured in 515 (80%) of these children.Results:For the same BMI, %BF was lower in Pacific Island (P<0.0001) and Māori (P<0.0001) girls compared with European but for boys there were no ethnic differences. Cross-sectional analysis across ages using Hattori charts clearly showed sexual dimorphism with girls having a higher FMI, FFMI and BMI than boys by the age of 13 year. Both Pacific girls and boys showed upward trends in FFMI and FMI with age that were significantly higher than those of the other ethnicities. Adjusting for age, sex and ethnicity, %BF was a better predictor (R2=0.090, P=0.0002) of total cholesterol than BMI (R2=0.061, P=0.049) or waist (R2=0.075, P=0.013) while FFMI was the best predictor of HDL cholesterol (R2=0.15, P<0.0001) and waist was the best predictor of the total cholesterol/HDL cholesterol ratio (R2=0.17, P<0.0001).Conclusions:Measurements of body fat and indices of body fatness additional to BMI in multiethnic paediatric populations allow changes in fat mass and FFM to be tracked and improve the ability to predict dyslipidaemia.European Journal of Clinical Nutrition (2009) 63, 627–633; doi:10.1038/ejcn.2008.15; published online 27 February 2008 [ABSTRACT FROM AUTHOR]