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Availability of sophisticated statistical modelling for developing robust reference equations has improved interpretation of lung function results. In 2012, the Global Lung function Initiative(GLI) published the first global all-age, multi-ethnic reference equations for spirometry but these lacked equations for those originating from the Indian subcontinent (South-Asians). The aims of this study were to assess the extent to which existing GLI-ethnic adjustments might fit South-Asian paediatric spirometry data, assess any similarities and discrepancies between South-Asian datasets and explore the feasibility of deriving a suitable South-Asian GLI-adjustment.\ud \ud Methods\ud \ud Spirometry datasets from South-Asian children were collated from four centres in India and five within the UK. Records with transcription errors, missing values for height or spirometry, and implausible values were excluded(n = 110).\ud \ud Results\ud \ud Following exclusions, cross-sectional data were available from 8,124 children (56.3% male; 5–17 years). When compared with GLI-predicted values from White Europeans, forced expired volume in 1s (FEV1) and forced vital capacity (FVC) in South-Asian children were on average 15% lower, ranging from 4–19% between centres. By contrast, proportional reductions in FEV1 and FVC within all but two datasets meant that the FEV1/FVC ratio remained independent of ethnicity. The ‘GLI-Other’ equation fitted data from North India reasonably well while ‘GLI-Black’ equations provided a better approximation for South-Asian data than the ‘GLI-White’ equation. However, marked discrepancies in the mean lung function z-scores between centres especially when examined according to socio-economic conditions precluded derivation of a single South-Asian GLI-adjustment.\ud \ud Conclusion\ud \ud Until improved and more robust prediction equations can be derived, we recommend the use of ‘GLI-Black’ equations for interpreting most South-Asian data, although ‘GLI-Other’ may be more appropriate for North Indian data. Prospective data collection using standardised protocols to explore potential sources of variation due to socio-economic circumstances, secular changes in growth/predictors of lung function and ethnicities within the South-Asian classification are urgently required.

Background Bioelectrical Impedance Analysis (BIA) has the potential to be used widely as a method of assessing body fatness and composition, both in clinical and community settings. BIA provides bioelectrical properties, such as whole-body impedance which ideally needs to be calibrated against a gold-standard method in order to provide accurate estimates of fat-free mass. UK studies in older children and adolescents have shown that, when used in multi-ethnic populations, calibration equations need to include ethnic-specific terms, but whether this holds true for younger children remains to be elucidated. The aims of this study were to examine ethnic differences in body size, proportions and composition in children aged 5 to 11 years, and to establish the extent to which such differences could influence BIA calibration. Methods In a multi-ethnic population of 2171 London primary school-children (47% boys; 34% White, 29% Black African/Caribbean, 25% South Asian, 12% Other) detailed anthropometric measurements were performed and ethnic differences in body size and proportion were assessed. Ethnic differences in fat-free mass, derived by deuterium dilution, were further evaluated in a subsample of the population (n = 698). Multiple linear regression models were used to calibrate BIA against deuterium dilution. Results In children

As active commuting levels continue to decline among primary schoolchildren, evidence about which built environmental characteristics influence walking or cycling to school remains inconclusive and is strongly context-dependent. This study aimed to identify the objective built environmental drivers of, and barriers to, active commuting to school for a multi-ethnic sample of 1,889 healthy primary schoolchildren (aged 5-11) in London, UK. Using cross-sectional multilevel ordered logistic regression modelling, supported by the spatial exploration of built environmental characteristics through cartography, the objective built environment was shown to be strongly implicated in children's commuting behaviour. In line with earlier research, proximity to school emerged as the prime variable associated with the choice for active commuting. However, other elements of the urban form were also significantly associated with children's use of active or passive modes of transport. High levels of accidents, crime and air pollution along the route to school were independently correlated with a lower likelihood of children walking or cycling to school. Higher average and minimum walkability and higher average densities of convenience stores along the way were independently linked to higher odds of active commuting. The significance of the relations for crime, air pollution and walkability disappeared in the fully-adjusted model including all built environmental variables. In contrast, relationships with proximity, traffic danger and the food environment were maintained in this comprehensive model. Black children, pupils with obesity, younger participants and those from high socioeconomic families were less likely to actively commute to school. There is thus a particular need to ensure that roads with high volumes of actively commuting children are kept safe and clean, and children's exposure to unhealthy food options along the way is limited. Moreover, as short commuting distances are strongly correlated with walking or cycling, providing high-quality education near residential areas might incite active transport to school.