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Objectives: The prospective cohort design is an important research design, but a common challenge is missing data. The purpose of this study is to compare three approaches to managing missing data, the pairwise (n = 1386 children), the partial or modified pairwise (n = 1019) and the listwise (n = 546), to characterize the trajectories of children's free sugars intake (FSI) across early childhood. Methods: By applying the Group‐based Trajectory Model Technique to three waves of data collected from a prospective cohort study of South Australian children, this study examined the three approaches in managing missing data to validate and discuss children's FSI trajectories. Results: Each approach identified three distinct trajectories of child's FSI from 1 to 5 years of age: (1) 'low and fast increasing', (2) 'moderate and increasing' and (3) 'high and increasing'. The trajectory memberships were consistent across the three approaches, and were for the pairwise scenario (1) 15.1%, (2) 68.3% and (3) 16.6%; the partial or modified pairwise (1) 15.9%, (2) 64.1% and (3) 20.0%; and the listwise (1) 14.9%, (2) 64.9% and (3) 20.2% of children. Conclusions: Given the comparability of the findings across the analytical approaches and the samples' characteristics between baseline and across different data collection waves, it is recommended that the pairwise approach be used in future analyses to optimize the sample size and statistical power when examining the relationship between FSI in the first years of life and health outcome such as dental caries. [ABSTRACT FROM AUTHOR]

Objective The association between and commonality of risk factors for poor self-rated oral health (SROH) and general health (SRGH) among new mothers has not been reported. The purpose of this paper is to assess the commonality of risk factors for poor SROH and SRGH, and self-reported obesity and dental pain, among a population-based sample of new mothers in Australia. It also investigated health conditions affecting new mothers’ general health. Methods Data collected at baseline of a population-based birth cohort was used. Mothers of newborns in Adelaide were approached to participate. Mothers completed a questionnaire collecting data on socioeconomic status (SES), health behaviours, dental pain, SROH, self-reported height and weight and SRGH. Analysis was conducted sequentially from bivariate to multivariable regression to estimate prevalence rate (PR) of reporting poor/fair SROH and SRGH. Results of the 1895 new mothers, some 21 and 6% rated their SROH and SRGH as poor/fair respectively. Dental pain was associated with low income and smoking status, while being obese was associated with low SES, low education and infrequent tooth brushing. SROH and SRGH was associated with low SES, smoking, and dental pain. SROH was also associated with SRGH [PR: 3.06 (2.42-3.88)]. Conclusion for practice There was a commonality of factors associated with self-rated oral health and general health. Strong associations between OH and GH were also observed. Given the importance of maternal health for future generations, there would be long-term societal benefit from addressing common risk factors for OH and GH in integrated programs. [ABSTRACT FROM AUTHOR]

The article offers information on the online Bring a Healthy Lunch Box to Work Challenge, a strategy to implement recommendations of the Australian Dietary Guidelines to motivate adults in workplaces to make small, incremental changes toward a healthier packed lunch. It mentions the challenges for increasing the physical activity in the workplace and to increase the number of healthy food choices in lunchboxes. It also mentions that the challenge was evaluated by pooled electronic survey.

We examined associations between dietary patterns at 12 months, characterised using multiple methodologies, and risk of obesity and early childhood caries (ECC) at 24-36 months. Participants were Australian toddlers (n = 1170) from the Study of Mothers' and Infants' Life Events affecting oral health (SMILE) birth cohort. Principal Components Analysis (PCA) and the Dietary Guideline Index for Children and Adolescents (DGI-CA) were applied to dietary intake data (1, 2 or 3-days) at 12 months, and regression analysis used to examine associations of dietary patterns with body mass index Z -score and presence of ECC at 24-36 months. Two dietary patterns were extracted using PCA: family diet and cow's milk and discretionary combination . The mean DGI-CA score was 56 ± 13 (out of a possible 100). No statistically significant or clinically meaningful associations were found between dietary pattern or DGI-CA scores, and BMI Z -scores or ECC (n = 680). Higher cow's milk and discretionary combination pattern scores were associated with higher energy and free sugars intakes, and higher family diet pattern scores and DGI-CA scores with lower free sugars intakes. The association between dietary patterns and intermediate outcomes of free sugars and energy intakes suggests that obesity and/or ECC may not yet have manifested, and thus longitudinal investigation beyond two years of age is warranted.

Objective: Functional data analysis (FDA) is a forecasting approach that, to date, has not been applied to obesity, and that may provide more accurate forecasting analysis to manage uncertainty in public health. This paper uses FDA to provide projections of Body Mass Index (BMI), overweight and obesity in an Australian population through to 2019., Methods: Data from the South Australian Monitoring and Surveillance System (January 2003 to December 2012, n=51,618 adults) were collected via telephone interview survey. FDA was conducted in four steps: 1) age-gender specific BMIs for each year were smoothed using a weighted regression; 2) the functional principal components decomposition was applied to estimate the basis functions; 3) an exponential smoothing state space model was used for forecasting the coefficient series; and 4) forecast coefficients were combined with the basis function., Results: The forecast models suggest that between 2012 and 2019 average BMI will increase from 27.2 kg/m(2) to 28.0 kg/m(2) in males and 26.4 kg/m(2) to 27.6 kg/m(2) in females. The prevalence of obesity is forecast to increase by 6-7 percentage points by 2019 (to 28.7% in males and 29.2% in females)., Conclusions: Projections identify age-gender groups at greatest risk of obesity over time. The novel approach will be useful to facilitate more accurate planning and policy development., (© 2015 Public Health Association of Australia.)