The present study examined the association of contextual factors (social and food preparation location) with the energy density of meals and snacks consumed in a sample of young Australian adults (18–30 years old) identified using wearable camera technology. Over three consecutive days, a subsample of young adults wore a wearable camera that captured images in 30 s intervals. Eating episodes from 133 participants were annotated for preparation location and social context (covering social interaction and screen use). Over the same period, participants completed daily 24 h recalls. The nutritional composition of meals and snacks was calculated by matching the items identified in the camera to the 24 h recall using time and date stamps. Self-reported data (weight and height) was used to calculate body mass index and (residential postcode) to assign socio-economic status. The association of context and demographic factors with energy density was determined using a mixed linear regression model employing the bootstrap method with bias-corrected and accelerated. In total, 1817 eating episodes were included in the analysis (n 8 preparation unclear and n 15 food components could not be identified excluded). Food prepared within the home was 1⋅1 kJ/g less energy-dense than other preparation locations. Lunches (CI −1⋅7 to −0⋅3) and dinners (CI −1⋅6 to −0⋅5) were both 1⋅0 kJ/g lower in energy density than breakfasts. Snacks were 3⋅5 kJ/g (CI 2⋅8–4⋅1) more energy-dense than breakfasts. Food prepared outside the home and food consumption during snacking appear to be adversely contributing to energy-dense food intake.

The revised Dietary Guideline Index (DGI-2013) scores individuals’ diets according to their compliance with the Australian Dietary Guideline (ADG). This cross-sectional study assesses the diet quality of 794 community-dwelling men aged 74 years and older, living in Sydney, Australia participating in the Concord Health and Ageing in Men Project; it also examines sociodemographic and lifestyle factors associated with DGI-2013 scores; it studies associations between DGI-2103 scores and the following measures: homoeostasis model assessment – insulin resistance, LDL-cholesterol, HDL-cholesterol, TAG, blood pressure, waist:hip ratio, BMI, number of co-morbidities and medications and frailty status while also accounting for the effect of ethnicity in these relationships. Median DGI-2013 score was 93·7 (54·4, 121·2); most individuals failed to meet recommendations for vegetables, dairy products and alternatives, added sugar, unsaturated fat and SFA, fluid and discretionary foods. Lower education, income, physical activity levels and smoking were associated with low scores. After adjustments for confounders, high DGI-2013 scores were associated with lower HDL-cholesterol, lower waist:hip ratios and lower probability of being frail. Proxies of good health (fewer co-morbidities and medications) were not associated with better compliance to the ADG. However, in participants with a Mediterranean background, low DGI-2013 scores were not generally associated with poorer health. Older men demonstrated poor diet quality as assessed by the DGI-2013, and the association between dietary guidelines and health measures and indices may be influenced by ethnic background.

Animal-source foods (ASF) have the potential to enhance the nutritional adequacy of cereal-based diets in low- and middle-income countries, through the provision of high-quality protein and bioavailable micronutrients. The development of guidelines for including ASF in local diets requires an understanding of the nutrient content of available resources. This article reviews food composition tables (FCT) used in sub-Saharan Africa, examining the spectrum of ASF reported and exploring data sources for each reference. Compositional data are shown to be derived from a small number of existing data sets from analyses conducted largely in high-income nations, often many decades previously. There are limitations in using such values, which represent the products of intensively raised animals of commercial breeds, as a reference in resource-poor settings where indigenous breed livestock are commonly reared in low-input production systems, on mineral-deficient soils and not receiving nutritionally balanced feed. The FCT examined also revealed a lack of data on the full spectrum of ASF, including offal and wild foods, which correspond to local food preferences and represent valuable dietary resources in food-deficient settings. Using poultry products as an example, comparisons are made between compositional data from three high-income nations, and potential implications of differences in the published values for micronutrients of public health significance, including Fe, folate and vitamin A, are discussed. It is important that those working on nutritional interventions and on developing dietary recommendations for resource-poor settings understand the limitations of current food composition data and that opportunities to improve existing resources are more actively explored and supported.

A single question (SQ) and a twenty-eight-item FFQ to measure takeaway meal intake were compared with two 7-d estimated food records (EFR; reference method). Test methods were completed after the reference period and repeated 6–8 d later for repeatability. The SQ asked about intake of high-SFA takeaway meals. FFQ items included low- and high-SFA meals. Test methods were compared with EFR for sensitivity, specificity, and positive and negative predictive values, using a goal of ≤1 high-SFA weekly takeaway meals. Bland–Altman analyses were used to check agreement between measurement approaches, the κ coefficient was used to summarise the observed level of agreement, and Spearman’s correlation was used to assess the degree to which instruments ranked individuals. Young adults were recruited from two universities, and 109 participants (61 % female) completed the study. The mean age was 24·4 (sd 4·9) years, and the mean BMI was 23·5 (sd 3·7) kg/m2. The SQ and the FFQ had a sensitivity of 97 and 83 % and a specificity of 46 and 92 %, respectively. Both methods exhibited moderate correlation for measuring total and high-SFA takeaway meal intakes (rs ranging from 0·64 to 0·80). Neither instrument could measure precise, absolute intake at the group or individual level. Test methods ranged from fair (κw=0·24) to moderate agreement (κw=0·59). The repeatability for all was acceptable. The FFQ identified excessive high-SFA takeaway meal intake and measured individuals’ category for total and high-SFA takeaway intakes. Both methods are suitable for ranking individuals for total or high-SFA takeaway meal intakes.

Automation of dietary assessment can reduce limitations of established methodologies, by alleviating participant and researcher burden. Designed as a research tool, the electronic Dietary Intake Assessment (e-DIA) is a food record in mobile phone application format. The present study aimed to examine the relative validity of the e-DIA with the 24-h recall method to estimate intake of food groups. A sample of eighty university students aged 19–24 years recorded 5 d of e-DIA and 3 d of recall within this 5-d period. The three matching days of dietary data were used for analysis. Food intake data were disaggregated and apportioned to one of eight food groups. Median intakes of food groups were similar between the methods, and strong correlations were found (mean: 0·79, range: 0·69–0·88). Cross-classification by tertiles produced a high level of exact agreement (mean: 71 %, range: 65–75 %), and weighted κ values were moderate to good (range: 0·54–0·71). Although mean differences (e-DIA–recall) were small (range: –13 to 23 g), limits of agreement (LOA) were relatively large (e.g. for vegetables, mean difference: –4 g, LOA: –159 to 151 g). The Bland–Altman plots showed robust agreement, with minimum bias. This analysis supports the use of e-DIA as an alternative to the repeated 24-h recall method for ranking individuals’ food group intake.

Supermarket receipts have the potential to provide prospective, objective information about the household food supply. The aim of this study was to develop an index to estimate population diet quality using food purchase data. Supermarket receipt data of 1 month were available for 836 adults from a corporate office of a large retail chain. Participants were aged 19–65 years (mean 37·6 (sd 9·3) years), 56 % were female and 63 % were overweight or obese. A scoring system (Healthy Trolley Index (HETI)) was developed to compare food expenditure with the Australian Guide to Healthy Eating. Monthly expenditure per food group, as a proportion of total food expenditure, was compared with food group recommendations, and a HETI score was calculated to estimate overall compliance with guidelines. Participants spent the greatest proportion on discretionary foods, which are high in fat/sugar (34·8 %), followed by meat including beef and chicken (17·0 %), fresh and frozen vegetables (13·5 %) and dairy foods (11·3 %). The average HETI score ranged from 22·6 to 93·1 (out of 100, mean 58·8 (sd 10·9)). There was a stepwise decrease in expenditure on discretionary foods by increasing HETI quintile, whereas expenditure on fruit and vegetables increased with HETI quintile (P<0·001). The HETI score was lower in obese compared with normal-weight participants (55·9 v. 60·3; P<0·01). Obese participants spent more on discretionary foods (38·3 v. 32·7 %; P<0·01) and less on fruits and vegetables (19·3 v. 22·2 %; P<0·01). The HETI may be a useful tool to describe supermarket purchasing patterns and quality of the household food supply with application for consumer feedback to assist improved quality of foods purchased.

The aim of the present study was to examine the associations of sugary drink consumption and its substitution with alternative beverages with body weight gain among young children predisposed to future weight gain. Secondary analysis of the Healthy Start Study, a 1·5-year randomised controlled trial designed to prevent overweight among Danish children aged 2−6 years (n 366), was carried out. Multivariate linear regression models were used to investigate the associations of beverage consumption with change in body weight (Δweight) or BMI(ΔBMI) z-score. Substitution models were used to extrapolate the influence of replacing sugary drinks with alternative beverages (water, milk and diet drinks) on Δweight or ΔBMI z-score. Sugary drink intake at baseline and substitution of sugary drinks with milk were associated with both Δweight and ΔBMI z-score. Every 100 g/d increase in sugary drink intake was associated with 0·10 kg and 0·06 unit increases in body weight (P=0·048) and BMI z-score (P=0·04), respectively. Substitution of 100 g/d sugary drinks with 100 g/d milk was inversely associated with Δweight (β=−0·16 kg; P=0·045) and ΔBMI z-score (β=−0·07 units; P=0·04). The results of this study suggest that sugary drink consumption was associated with body weight gain among young children with high predisposition for future overweight. In line with the current recommendations, sugary drinks, whether high in added or natural sugar, should be discouraged to help prevent childhood obesity. Milk may be a good alternative to sugary drinks with regard to weight management among young obesity-predisposed children.

Previous research shows that older men tend to have lower nutritional intakes and higher risk of under-nutrition compared with younger men. The objectives of this study were to describe energy and nutrient intakes, assess nutritional risk and investigate factors associated with poor intake of energy and key nutrients in community-dwelling men aged ≥75 years participating in the Concord Health and Ageing in Men Project – a longitudinal cohort study on older men in Sydney, Australia. A total of 794 men (mean age 81·4 years) had a detailed diet history interview, which was carried out by a dietitian. Dietary adequacy was assessed by comparing median intakes with nutrient reference values (NRV): estimated average requirement, adequate intake or upper level of intake. Attainment of NRV of total energy and key nutrients in older age (protein, Fe, Zn, riboflavin, Ca and vitamin D) was incorporated into a ‘key nutrients’ variable dichotomised as ‘good’ (≥5) or ‘poor’ (≤4). Using logistic regression modelling, we examined associations between key nutrients with factors known to affect food intake. Median energy intake was 8728 kJ (P5=5762 kJ, P95=12 303 kJ), and mean BMI was 27·7 (sd 4·0) kg/m2. Men met their NRV for most nutrients. However, only 1 % of men met their NRV for vitamin D, only 19 % for Ca, only 30 % for K and only 33 % for dietary fibre. Multivariate logistic regression analysis showed that only country of birth was significantly associated with poor nutritional intake. Dietary intakes were adequate for most nutrients; however, only half of the participants met the NRV of ≥5 key nutrients.

Poor vitamin B12 status may lead to the development of cognitive decline and dementia but there is a large variation in the quality, design of and results reported from these investigations. We have undertaken a systematic review of the evidence for the association between vitamin B12 status and cognitive decline in older adults. A database search of the literature to 2011 was undertaken, using keywords related to vitamin B12 and cognition. All prospective cohort studies assessing the association of serum vitamin B12 or biomarkers were included. Quality assessment and extraction of the data were undertaken by two researchers. The quality assessment tool assigns a positive, neutral or negative rating. Of 3772 published articles, thirty-five cohort studies (n 14 325 subjects) were identified and evaluated. No association between serum vitamin B12 concentrations and cognitive decline or dementia was found. However, four studies that used newer biomarkers of vitamin B12 status (methylmalonic acid and holotranscobalamin (holoTC)) showed associations between poor vitamin B12 status and the increased risk of cognitive decline or dementia diagnosis. In general, the studies were of reasonable quality (twenty-one positive, ten neutral and four negative quality) but of short duration and inadequate subject numbers to determine whether an effect exists. Future studies should be of adequate duration (at least 6 years), recruit subjects from the seventh decade, choose markers of vitamin B12 status with adequate specificity such as holoTC and/or methylmalonic acid and employ standardised neurocognitive assessment tools and not screening tests in order to ascertain any relationship between vitamin B12 status and cognitive decline.

Past investigation of diet in relation to disease or mortality has tended to focus on individual nutrients. However, there has been a recent shift to now focus on overall patterns of food intake. The present study aims to investigate the relationship between diet quality reflecting adherence to dietary guidelines and mortality in a sample of older Australians, and to report on the relationship between core food groups and diet quality. This was a population-based cohort study of persons aged 49 years or older at baseline, living in two postcode areas west of Sydney, Australia. Baseline dietary data were collected during 1992–4, from 2897 people using a 145-item Willett-derived FFQ. A modified version of the Healthy Eating Index for Australians was developed to determine diet quality scores. The Australian National Death Index provided 15-year mortality data using multiple data linkage steps. Hazard risk (HR) ratios and 95 % CI for mortality were assessed for diet quality. Subjects in quintile 5 (highest) of the Total Diet Score had a 21 % reduced risk of all-cause mortality (HR 0·79, 95 % CI 0·63, 0·98, Ptrend= 0·04) compared with those in quintile 1 (lowest) after multivariate adjustment. The present study provides longitudinal support for a reduced risk of all-cause mortality in an older population who have greater compliance with published dietary guidelines.

The prevalence of obesity continues to rise with many factors contributing to energy imbalance. Leisure-time physical activity (LTPA) has been proposed as one solution to counteract increasing energy intakes. The present study determined whether age, birth cohort and period of survey had independent effects on time, volume and energy expended in LTPA by Australian adults from 1990 to 2005. Adults were categorised into twelve age groups (5-year intervals from 20–24 years to >75 years), four survey periods (1990, 1995, 2000 and 2005) and fifteen birth cohorts (5-year intervals from pre-1916 to 1985). Time spent in three categories of LTPA was determined and metabolic equivalent (MET) values of 3·3, 4·0 and 8·0 were assigned for walking, moderate and vigorous activities, respectively, to calculate daily volume (MET minutes). Energy expended in LTPA was calculated using estimated BMR (from self-reported weight and published formulae), multiplied by the MET value. Regression models were fitted to the data. Age and period had independent effects on duration, volume and energy expenditure of LTPA for both males (P < 0·01) and females (P < 0·01), while birth cohort had independent effects for males only such that all three LTPA factors declined with recency of birth cohort (P < 0·01). This indicates that more recent birth cohorts of males may need to be targeted to increase LTPA, but as duration, volume and energy expended in leisure time have been declining since 1990, both the sexes may benefit from the promotion of increased LTPA.