(1) Background: The Paleolithic diet is popular in Australia, however, limited literature surrounds the dietary pattern. Our primary aim was to compare the Paleolithic diet with the Australian Guide to Healthy Eating (AGHE) in terms of anthropometric, metabolic and cardiovascular risk factors, with a secondary aim to examine the macro and micronutrient composition of both dietary patterns; (2) Methods: 39 healthy women (mean ± SD age 47 ± 13 years, BMI 27 ± 4 kg/m2) were randomised to either the Paleolithic (n = 22) or AGHE diet (n = 17) for four weeks. Three-day weighed food records, body composition and biochemistry data were collected pre and post intervention; (3) Results: Significantly greater weight loss occurred in the Paleolithic group (−1.99 kg, 95% CI −2.9, −1.0), p < 0.001). There were no differences in cardiovascular and metabolic markers between groups. The Paleolithic group had lower intakes of carbohydrate (−14.63% of energy (E), 95% CI −19.5, −9.7), sodium (−1055 mg/day, 95% CI −1593, −518), calcium (−292 mg/day 95% CI −486.0, −99.0) and iodine (−47.9 μg/day, 95% CI −79.2, −16.5) and higher intakes of fat (9.39% of E, 95% CI 3.7, 15.1) and β-carotene (6777 μg/day 95% CI 2144, 11410) (all p < 0.01); (4) Conclusions: The Paleolithic diet induced greater changes in body composition over the short-term intervention, however, larger studies are recommended to assess the impact of the Paleolithic vs. AGHE diets on metabolic and cardiovascular risk factors in healthy populations.

Image-based dietary records have limited evidence evaluating their performance and use among adults with a chronic disease. This study evaluated the performance of a 3-day mobile phone image-based dietary record, the Nutricam Dietary Assessment Method (NuDAM), in adults with type 2 diabetes mellitus (T2DM). Criterion validity was determined by comparing energy intake (EI) with total energy expenditure (TEE) measured by the doubly-labelled water technique. Relative validity was established by comparison to a weighed food record (WFR). Inter-rater reliability was assessed by comparing estimates of intake from three dietitians. Ten adults (6 males, age: 61.2 ± 6.9 years old, BMI: 31.0 ± 4.5 kg/m2) participated. Compared to TEE, mean EI (MJ/day) was significantly under-reported using both methods, with a mean ratio of EI:TEE 0.76 ± 0.20 for the NuDAM and 0.76 ± 0.17 for the WFR. Correlations between the NuDAM and WFR were mostly moderate for energy (r = 0.57), carbohydrate (g/day) (r = 0.63, p < 0.05), protein (g/day) (r = 0.78, p < 0.01) and alcohol (g/day) (rs = 0.85, p < 0.01), with a weaker relationship for fat (g/day) (r = 0.24). Agreement between dietitians for nutrient intake for the 3-day NuDAM (Intra-class Correlation Coefficient (ICC) = 0.77–0.99) was lower when compared with the 3-day WFR (ICC = 0.82–0.99). These findings demonstrate the performance and feasibility of the NuDAM to assess energy and macronutrient intake in a small sample. Some modifications to the NuDAM could improve efficiency and an evaluation in a larger group of adults with T2DM is required.

We evaluated a mobile phone application (Nutricam) for recording dietary intake. It allowed users to capture a photograph of food items before consumption and store a voice recording to explain the contents of the photograph. This information was then sent to a website where it was analysed by a dietitian. Ten adults with type 2 diabetes (BMI 24.1-47.9 kg/m(2)) recorded their intake over a three-day period using both Nutricam and a written food diary. Compared to the food diary, energy intake was under-recorded by 649 kJ (SD 810) using the mobile phone method. However, there was no trend in the difference between dietary assessment methods at levels of low or high energy intake. All subjects reported that the mobile phone system was easy to use. Six subjects found that the time taken to record using Nutricam was shorter than recording using the written diary, while two reported that it was about the same. The level of detail provided in the voice recording and food items obscured in photographs reduced the quality of the mobile phone records. Although some modifications to the mobile phone method will be necessary to improve the accuracy of self-reported intake, the system was considered an acceptable alternative to written records and has the potential to be used by adults with type 2 diabetes for monitoring dietary intake by a dietitian.

Aim:  Aboriginal people living in remote communities experience high levels of chronic illness partly as a result of diet‐related body mass index above 25 kg/m2. Remote stores are typically the only source of food and store nutrition policies are effective in enabling better health for community residents by changing product lines. The aim of the present study was to examine trends in purchasing patterns of sugar‐sweetened water‐based beverages in a remote Aboriginal community store following the implementation of a community‐developed store nutrition policy. Methods:  Documents outlining the objectives and strategies of the store policy were examined. Store sales data were quantified to determine changes in purchasing patterns, volume of beverages sold, sugar and energy purchased before and after the withdrawal of the three highest selling sugar‐sweetened water‐based beverages. Results:  The community‐developed policy was effective in implementing changes to product lines sold in the remote Aboriginal store. The withdrawal of the three top selling sugar‐sweetened water‐based beverages did not affect the total volume of all beverages sold but a shift in purchasing trends towards beverages with lower or zero sugar content resulted in a reduction in sugar and kilojoules consumed through water‐based beverages. Conclusion:  The approach of a community‐driven store nutrition policy described here was successful and could be applied to other products in store that provide excess kilojoules with minimal nutritional benefit. The policy and aspects of implementation could also be applied in other remote Aboriginal communities.

Secondary analysis of the 2007 Australian National Children's Nutrition and Physical Activity survey was undertaken to assess the intake and food sources of EPA, DPA and DHA (excluding supplements) in 4,487 children aged 2-16 years. An average of two 24-h dietary recalls was analysed for each child and food sources of EPA, DPA and DHA were assessed using the Australian nutrient composition database called AUSNUT 2007. Median (inter quartile range, IQR) for EPA, DPA and DHA intakes (mg/day) for 2-3, 4-8, 9-13, 14-16 year were: EPA 5.3 (1.5-14), 6.7 (1.8-18), 8.7 (2.6-23), 9.8 (2.7-28) respectively; DPA 6.2 (2.2-14), 8.2 (3.3-18), 10.8 (4.3-24), 12.2 (5-29) respectively; and DHA 3.9 (0.6-24), 5.1 (0.9-26), 6.8 (1.1-27), 7.8 (1.5-33) respectively. Energy-adjusted intakes of EPA, DPA and DHA in children who ate fish were 7.5, 2 and 16-fold higher, respectively (P < 0.001) compared to those who did not eat fish during the 2 days of the survey. Intake of total long chain n-3 PUFA was compared to the energy adjusted suggested dietary target (SDT) for Australian children and 20 % of children who ate fish during the 2 days of the survey met the SDT. Fish and seafood products were the largest contributors to DHA (76 %) and EPA (59 %) intake, while meat, poultry and game contributed to 56 % DPA. Meat consumption was 8.5 times greater than that for fish/ seafood. Australian children do not consume the recommended amounts of long chain omega-3 fatty acids, especially DHA, which could be explained by low fish consumption. IQR) for EPA, DPA and DHA intakes (mg/d) for 2-3y, 4-8y, 9-13y, 14-16y were: EPA 5.3 (1.5-14), 6.7 (1.8-18), 8.7 (2.6-23), 9.8 (2.7-28) respectively; DPA 6.2 (2.2-14), respectively. Energy-adjusted intakes of EPA, DPA and DHA in children who ate fish were 7.5, 2 and 16-fold higher, respectively (P<0.001) compared to those who did not eat fish during the two days of the survey. Intake of total long chain n-3 PUFA was compared to the energy adjusted suggested dietary target (SDT) for Australian children and 20% of children who ate fish during the two days of the survey met the SDT. Fish and seafood products were the largest contributors to DHA (76%) and EPA (59%) intake, while meat, poultry and game contributed to 56% DPA. Meat was consumed 8.5 times greater than fish/seafood. Australian children do not consume the recommended amounts of long chain omega-3 fatty acids, especially DHA, which could be explained by low fish consumptions.