Gina Leslie Ambrosini

Issue Addressed: This study explored trends in public support for obesity prevention policies in Western Australia (WA). Methods: A series of cross-sectional surveys of a representative sample of WA adults aged 25-49 years (N = 11 534) were undertaken between 2012 and 2020 as part of an evaluation of the LiveLighter (R) mass media campaign, a component of a statewide healthy lifestyle education and promotion programme. Computer-assisted telephone interviews were used to gauge support for a range of obesity prevention initiatives that could be implemented by government. Results: A majority of respondents supported a range of obesity prevention policies, including taxes on sugary drinks, urban planning regulations, food labelling and packaging regulations, restrictions on advertising and sponsorship, bans on the sale and marketing of unhealthy food and drink in retail environments and support for education and campaigns. Obesity prevention policies were highly supported by women, people with a healthy weight, and those who had completed secondary school. Support for regulation was high compared to other studies. Notably, there were significant increases in support between baseline and 2020 for 'taxing soft drinks and using the money to reduce the cost of healthy food' (72% cf. 80%) and 'restricting junk food promotions/advertisements on public transport' (73% cf. 83%). Conclusions: There is substantial public support for regulatory action on obesity prevention in WA, providing strong rationale for government interventions to improve nutrition and reduce obesity. The LiveLighter (R) programme may have contributed to increases in support for obesity prevention policies in WA. So What? There is potential to implement robust obesity prevention policies in WA.

High protein intake in young children is associated with excess gains in weight and body fat, but the specific role of different protein sources has yet to be described. The study aimed to investigate the role of different types of protein in the post-weaning stage on weight, BMI and overweight/obesity at 60 months. Intakes of animal, dairy and plant protein and a dietary pattern characterising variation in protein types at 21 months of age were estimated using a 3-d diet diary in a cohort of 2154 twins; weight and height were recorded every 3 months from birth to 60 months. Longitudinal mixed-effect models investigated the associations between sources of protein intake or dietary pattern scores and BMI, weight and overweight/obesity from 21 months up to 60 months. Adjusting for confounders, dairy protein intake at 21 months was positively associated with greater weight (46 (95 % CI 21, 71) g and BMI up to 60 months (0·04 (95 % CI 0·004, 0·070) kg/m²) and the odds of overweight/obesity at 3 years (OR 1·12; 95 % CI 1·00, 1·24). Milk showed associations of similar magnitude. A dietary pattern low in dairy protein and high in plant protein was associated with lower weight gain up to 60 months, but not overweight/obesity. Intake of dairy products in early childhood is most strongly associated with weight gain, compared with other protein sources. A dietary pattern characterised by lower protein intake and greater protein source diversity at 2 years may confer a lower risk of excess weight gain.

Relatively little is known about dietary changes and their relationships with weight change during behavioural weight loss interventions. In a secondary analysis of data from a multicentre RCT, we investigated whether greater improvements in diet would be achieved by overweight adults following a 12 month group-based commercial weight loss programme (CP) than those receiving standard care (SC) in primary practice, and if these dietary changes were associated with greater weight loss. Adults with a BMI 27–35 kg/m2 and >1 risk factor for obesity-related disorders were recruited in study centres in Australia and the UK during 2007–2008. Dietary intake and body weight were measured at baseline, 6 and 12 months. Linear mixed effects models compared mean changes in dietary macronutrient intake, fibre density and energy density over time between groups, and their relationships with weight loss. The CP group demonstrated greater mean weight loss than the SC group at 6 months (3.3 kg, 95% CI: 2.2, 4.4) and 12 months (3.3 kg, 95% CI: 2.1, 4.5). Diet quality improved in both intervention groups at 6 and 12 months. However, the CP group (n = 228) achieved significantly greater mean reductions in energy intake (mean difference; 95% CI: − 503 kJ/d; − 913, − 93), dietary energy density (− 0.48 MJ/g; − 0.81, − 0.16), total fat (− 6.9 g/d; − 11.9, − 1.8), saturated fat (− 3.3 g/d; − 5.4, − 1.1), and significantly greater mean increases in fibre density (0.30 g/MJ; 0.15, 0.44) at 6 months than the SC group (n = 239). Similar differences persisted at 12 months and the CP group showed greater mean increases in protein density (0.65 g/MJ). In both groups, weight loss was associated with increased fibre density (0.68 kg per g/MJ, 95% CI: 0.08, 1.27) and protein density (0.26 kg per g/MJ, 95% CI: 0.10, 0.41). Following a group-based commercial program led to greater improvements in diet quality than standard care. Increases in dietary protein and fibre density were independently associated with weight loss in both behavioural weight loss interventions. Greater increases in protein and fibre density in the commercial program likely contributed to their greater weight loss. ISRCTN: ISRCTN85485463 Registered 03/08/2007 Retrospectively Registered.

The relationships between food environments and dietary intake have been assessed via a range of methodologically diverse measures of spatial exposure to food outlets, resulting in a largely inconclusive body of evidence, limiting informed policy intervention. This systematic review aims to evaluate the influence of methodological choice on study outcomes by examining the within-study effect of availability (e.g., counts) versus accessibility (e.g., proximity) spatial exposure measures on associations with diet. (PROSPERO registration: CRD42018085250). PubMed, Web of Science, Scopus and ScienceDirect databases were searched for empirical studies from 1980 to 2017, in the English language, involving adults and reporting on the statistical association between a dietary outcome and spatial exposure measures of both availability and accessibility. Studies were appraised using an eight-point quality criteria with a narrative synthesis of results. A total of 205 associations and 44 relationships (i.e., multiple measures of spatial exposure relating to a particular food outlet type and dietary outcome) were extracted from 14 eligible articles. Comparative measures were dominated by counts (availability) and proximity (accessibility). Few studies compared more complex measures and all counts were derived from place-based measures of exposure. Sixteen of the 44 relationships had a significant effect involving an availability measure whilst only 8 had a significant effect from an accessibility measure. The largest effect sizes in relationships were mostly for availability measures. After stratification by scale, availability measure had the greatest effect size in 139 of the 176 pairwise comparisons. Of the 33% (68/205) of associations that reached significance, 53/68 (78%) were from availability measures. There was no relationship between study quality and reported study outcomes. The limited evidence suggests that availability measures may produce significant and greater effect sizes than accessibility measures. However, both availability and accessibility measures may be important concepts of spatial exposure depending on the food outlet type and dietary outcome examined. More studies reporting on multi-method effects are required to differentiate findings by the type of spatial exposure assessment and build an evidence base regarding the appropriateness and robustness of measures under different circumstances.

Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004–2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman’s rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen’s weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.

Dietary assessment methods that can provide high quality data while limiting participant burden and resource requirements in epidemiological research are highly sought after and continue to evolve. The use of mobile phone technology in research has increased rapidly over the last decade and offers multiple advantages to the researcher over traditional data collection methods. This study tested the acceptability and relative validity of a commercial smart phone application (app) for use as an epidemiological dietary assessment tool, compared with a traditional dietary assessment method. Study participants completed a 4-d food diary using a modified version of the Easy Diet Diary app and two 24-h dietary recalls during the same week, for comparison. At the end of data collection, participants completed a questionnaire on their experience with both methods. Average proportions of energy from macronutrients and fibre, iron, and calcium densities from the app and 24-h recalls were compared after log transformation, by calculating mean agreement, limits of agreement (LOA), and Pearson’s correlations. The prevalence of dietary under-reporting was compared in each method using the Goldberg method. A total of 50 adults (82% women) provided data for analysis (mean age, 31 y; mean BMI, 22.4 kg/m2; 14% overweight or obese). Participant feedback showed high levels of acceptance of the app; 83% preferred using the app to completing 24-h dietary recalls. The average difference in energy intake (mean agreement) between methods was 268 kJ/d. For all intakes except alcohol, the average difference between methods was not significantly different from zero. Most limits of agreement were within an acceptable range. The prevalence of dietary misreporting was similar in both methods. These findings demonstrate good feasibility for applying this commercially-developed smartphone app in epidemiological research.

Background: Although growing evidence suggests that dietary patterns associated with noncommunicable diseases in adulthood may develop early in life, when these are established, as well as their determinants, remains unclear.Methods: We examined determinants and tracking of a dietary pattern (DP) associated with metabolic risk and its key food groups among 860 adolescents in the Western Australian Pregnancy (Raine) Cohort study. Food intake was reported using a food frequency questionnaire (FFQ) at 14 and 17 years. Z‐scores for an ‘energy‐dense, high‐fat, low‐fibre’ DP were estimated by applying reduced rank regression at both ages. Tracking was based on the predictive value (PV) of remaining in the DPZ‐score or food intake quartile at 14 and 17 years. Early‐life exposures included: maternal age; maternal pre‐pregnancy body mass index; parent smoking status during pregnancy; and parent socio‐economic position (SEP) at 14 and 17 years. Associations between the DPZ‐scores, early‐life factors and SEP were analysed using regression analysis.Results: Dietary tracking was strongest among boys with high DPZ‐scores, high intakes of processed meat, low‐fibre bread, crisps and savoury snacks (PV > 1) and the lowest intakes of vegetables, fruit and legumes. Lower maternal education (β = 0.09, P = 0.002 at 14 years; β = 0.14, P < 0.001 at 17 years) and lower maternal age at birth (β = 0.09, P = 0.003 at 14 years; β = 0.11, P = 0.004 at 17 years) were positively associated with higher DPZ‐scores.Conclusions: An energy‐dense, high‐fat, low‐fibre dietary pattern tracks more strongly among adolescent boys who have high scores for this pattern at 14 years of age. These findings highlight target foods and population subgroups for early interventions aiming to improve dietary behaviours.

Supporting patients to have healthy dietary behaviours contributes significantly to preventing and managing lifestyle-related chronic diseases. ‘Nutrition care’ refers to any practice provided by a health professional to support a patient to improve their dietary behaviours and subsequent health outcomes. Approximately 3% of consultations by Australian general practitioners (GPs) involve the provision of nutrition care. The aim of the present paper was to forecast the potential implications of a higher frequency of nutrition care by GPs. Evidence on the effect of improved dietary behaviours on chronic disease outcomes, number of Australian adults estimated to have poor dietary behaviours and effectiveness of GPs providing nutrition care were taken into consideration. Using hypertension as a case example, for GPs to provide nutrition care to all hypertensive adults who would benefit from improved dietary behaviours, GPs would need to provide nutrition care in a target rate of 4.85% of consultations or 4.5 million different patients each year. The target aligns with the existing priorities for supporting chronic-disease prevention and management in Australia by increasing the rate that brief lifestyle interventions are provided by primary health professionals. This conservative target presents a considerable challenge for GPs, support staff, researchers and policy makers, but can be used to inform future interventions to support nutrition care by GPs.