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Using data from a nationally generalisable birth cohort, we aimed to: (i) describe the cohort's adherence to national evidence-based dietary guidelines using an Infant Feeding Index (IFI) and (ii) assess the IFI's convergent construct validity, by exploring associations with antenatal maternal socio-demographic and health behaviours and with child overweight/obesity and central adiposity at age 54 months. Data were from the Growing Up in New Zealand cohort (n 6343). The IFI scores ranged from zero to twelve points, with twelve representing full adherence to the guidelines. Overweight/obesity was defined by BMI-for-age (based on the WHO Growth Standards). Central adiposity was defined as waist-to-height ratio > 90th percentile. Associations were tested using multiple linear regression and Poisson regression with robust variance (risk ratios, 95 % CI). Mean IFI score was 8·2 (sd 2·1). Maternal characteristics explained 29·1 % of variation in the IFI score. Maternal age, education and smoking had the strongest independent relationships with IFI scores. Compared with children in the highest IFI tertile, girls in the lowest and middle tertiles were more likely to be overweight/obese (1·46, 1·03, 2·06 and 1·56, 1·09, 2·23, respectively) and boys in the lowest tertile were more likely to have central adiposity (1·53, 1·02, 2·30) at age 54 months. Most infants fell short of meeting national Infant Feeding Guidelines. The associations between IFI score and maternal characteristics, and children's overweight/obesity/central adiposity, were in the expected directions and confirm the IFI's convergent construct validity. [ABSTRACT FROM AUTHOR]

Several early childhood obesity prediction models have been developed, but none for New Zealand's diverse 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. [ABSTRACT FROM AUTHOR]

The article focuses on the childhood exposure to neighborhood environments with wood and coal heated households and the onset of both respiratory and skin diseases. It mentions the analysis of 3461 children in which 1372 received respiratory, 2456 received dermatological, and 2750 received dermatological prescriptions; and also mentions living in an environment with higher density of wood and coal heated households is associated with an increased risk of dermatological medications.

Significant ethnic and socio-economic disparities exist in infectious diseases (IDs) rates in New Zealand, so accurate measures of these characteristics are required. This study compared methods of ascribing ethnicity and socio-economic status. Children in the Growing Up in New Zealand longitudinal cohort were ascribed to self-prioritised, total response and single-combined ethnic groups. Socio-economic status was measured using household income, and both census-derived and survey-derived deprivation indices. Rates of ID hospitalisation were compared using linked administrative data. Self-prioritised ethnicity was simplest to use. Total response accounted for mixed ethnicity and allowed overlap between groups. Single-combined ethnicity required aggregation of small groups to maintain power but offered greater detail. Regardless of the method used, Māori and Pacific children, and children in the most socio-economically deprived households had a greater risk of ID hospitalisation. Risk differences between self-prioritised and total response methods were not significant for Māori and Pacific children but single-combined ethnicity revealed a diversity of risk within these groups. Household income was affected by non-random missing data. The census-derived deprivation index offered a high level of completeness with some risk of multicollinearity and concerns regarding the ecological fallacy. The survey-derived index required extra questions but was acceptable to participants and provided individualised data. Based on these results, the use of single-combined ethnicity and an individualised survey-derived index of deprivation are recommended where sample size and data structure allow it. [ABSTRACT FROM AUTHOR]