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BackgroundWeb-based health interventions may be easier to access and time efficient relative to face-to-face interventions and therefore may be the most appropriate mode to engage young adults. ObjectiveThis study aims to investigate the impact of 3 different levels of personalized web-based dietary feedback and support on changes in diet quality. MethodsThe Advice, Ideas, and Motivation for My Eating (Aim4Me) study is a 12-month assessor-blinded, parallel-group randomized controlled trial evaluating the impact of 3 levels of web-based feedback on diet quality, measured using the Australian Recommended Food Score (ARFS). Participants (N=2570) will primarily be recruited via web-based methods and randomized to 1 of 3 groups. Group 1 (control) will receive the Healthy Eating Quiz, a web-based dietary assessment tool that generates a brief feedback report on diet quality. Individuals randomized to this group can use the brief feedback report to make positive dietary changes. Group 2 will receive the Australian Eating Survey, a web-based dietary assessment tool that generates a comprehensive feedback report on diet quality as well as macro- and micronutrient intake. Group 2 will use the comprehensive feedback report to assist in making positive dietary changes. They will also have access to the Aim4Me website with resources on healthy eating and tools to set goals and self-monitor progress. Group 3 will receive the same intervention as Group 2 (ie, the comprehensive feedback report) in addition to a tailored 30-min video consultation with an accredited practicing dietitian who will use the comprehensive feedback report to assist individuals in making positive dietary changes. The self-determination theory was used as the framework for selecting appropriate website features, including goal setting and self-monitoring. The primary outcome measure is change in diet quality. The completion of questionnaires at baseline and 3, 6, and 12 months will be incentivized with a monetary prize draw. ResultsAs of December 2019, 1277 participants have been randomized. ConclusionsThe web-based delivery of nutrition interventions has the potential to improve dietary intake of young adults. However, the level of support required to improve intake is unknown. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12618000325202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=374420 International Registered Report Identifier (IRRID)DERR1-10.2196/15999

BackgroundDietitians ideally should provide personally tailored nutrition advice to pregnant women. Provision is hampered by a lack of appropriate tools for nutrition assessment and counselling in practice settings. Smartphone technology, through the use of image-based dietary records, can address limitations of traditional methods of recording dietary intake. Feedback on these records can then be provided by the dietitian via smartphone. Efficacy and validity of these methods requires examination. ObjectiveThe aims of the Australian Diet Bytes and Baby Bumps study, which used image-based dietary records and a purpose-built brief Selected Nutrient and Diet Quality (SNaQ) tool to provide tailored nutrition advice to pregnant women, were to assess relative validity of the SNaQ tool for analyzing dietary intake compared with nutrient analysis software, to describe the nutritional intake adequacy of pregnant participants, and to assess acceptability of dietary feedback via smartphone. MethodsEligible women used a smartphone app to record everything they consumed over 3 nonconsecutive days. Records consisted of an image of the food or drink item placed next to a fiducial marker, with a voice or text description, or both, providing additional detail. We used the SNaQ tool to analyze participants’ intake of daily food group servings and selected key micronutrients for pregnancy relative to Australian guideline recommendations. A visual reference guide consisting of images of foods and drinks in standard serving sizes assisted the dietitian with quantification. Feedback on participants’ diets was provided via 2 methods: (1) a short video summary sent to participants’ smartphones, and (2) a follow-up telephone consultation with a dietitian. Agreement between dietary intake assessment using the SNaQ tool and nutrient analysis software was evaluated using Spearman rank correlation and Cohen kappa. ResultsWe enrolled 27 women (median age 28.8 years, 8 Indigenous Australians, 15 primiparas), of whom 25 completed the image-based dietary record. Median intakes of grains, vegetables, fruit, meat, and dairy were below recommendations. Median (interquartile range) intake of energy-dense, nutrient-poor foods was 3.5 (2.4-3.9) servings/day and exceeded recommendations (0-2.5 servings/day). Positive correlations between the SNaQ tool and nutrient analysis software were observed for energy (ρ=.898, P

BackgroundSelf-monitoring is an essential behavioral strategy for effective weight loss programs. Traditionally, self-monitoring has been achieved using paper-based records. However, technology is now more frequently used to deliver treatment programs to overweight and obese adults. Information technologies, such as the Internet and mobile phones, allow innovative intervention features to be incorporated into treatment that may facilitate greater adherence to self-monitoring processes, provide motivation for behavior change, and ultimately lead to greater weight loss success. ObjectiveThe objective of our study was to determine whether the consistency of self-monitoring differed between participants randomly assigned to a basic or an enhanced 12-week commercial Web-based weight loss program. MethodsWe randomly assigned a sample of 301 adults (mean age 42.3 years; body mass index 31.3 kg/m2; female 176/301, 58.5%) to the basic or enhanced group. The basic program included tools for self-monitoring (online food and exercise diary, and a weekly weigh-in log) with some feedback and reminders to weigh in (by text or email). The enhanced program included the basic components, as well as extra individualized feedback on self-monitoring entries and reminders (by text, email, or telephone) to engage with self-monitoring tools. We evaluated the level of self-monitoring by examining the consistency of self-monitoring of food, exercise, and weight during the 12 weeks. Consistency was defined as the number of weeks during which participants completed a criterion number of entries (ie, ≥3 days of online food or exercise diary records per week and ≥1 weigh-in per week). ResultsThe enhanced group’s consistency of use of self-monitoring tools was significantly greater than that of the basic group throughout the 12 weeks (median consistency for food 8 vs 3 weeks, respectively, P

BackgroundWeb-based approaches are an effective and convenient medium to deliver eHealth interventions. However, few studies have attempted to evaluate the accuracy of online self-reported weight, and only one has assessed the accuracy of online self-reported height and body mass index (BMI). ObjectiveThis study aimed to validate online self-reported height, weight, and calculated BMI against objectively measured data in young Australian adults. MethodsParticipants aged 18-35 years were recruited via advertisements on social media sites and reported their current height and weight as part of an online survey. They then subsequently had the same measures objectively assessed by a trained researcher. ResultsSelf-reported height was significantly overestimated by a mean of 1.36 cm (SD 1.93; P

BackgroundCommercial Web-based weight-loss programs are becoming more popular and increasingly refined through the addition of enhanced features, yet few randomized controlled trials (RCTs) have independently and rigorously evaluated the efficacy of these commercial programs or additional features. ObjectiveTo determine whether overweight and obese adults randomized to an online weight-loss program with additional support features (enhanced) experienced a greater reduction in body mass index (BMI) and increased usage of program features after 12 and 24 weeks compared to those randomized to a standard online version (basic). MethodsAn assessor-blinded RCT comparing 301 adults (male: n=125, 41.5%; mean age: 41.9 years, SD 10.2; mean BMI: 32.2 kg/m2, SD 3.9) who were recruited and enrolled offline, and randomly allocated to basic or enhanced versions of a commercially available Web-based weight-loss program for 24 weeks. ResultsRetention at 24 weeks was greater in the enhanced group versus the basic group (basic 68.5%, enhanced 81.0%; P=.01). In the intention-to-treat analysis of covariance with imputation using last observation carried forward, after 24 weeks both intervention groups had reductions in key outcomes with no difference between groups: BMI (basic mean –1.1 kg/m2, SD 1.5; enhanced mean –1.3 kg/m2, SD 2.0; P=.29), weight (basic mean –3.3 kg, SD 4.7; enhanced mean –4.0 kg, SD 6.2; P=.27), waist circumference (basic mean –3.1 cm, SD 4.6; enhanced mean –4.0 cm, SD 6.2; P=.15), and waist-to-height ratio (basic mean –0.02, SD 0.03; enhanced mean –0.02, SD 0.04, P=.21). The enhanced group logged in more often at both 12 and 24 weeks, respectively (enhanced 12-week mean 34.1, SD 28.1 and 24-week mean 43.1, SD 34.0 vs basic 12-week mean 24.6, SD 25.5 and 24-week mean 31.8, SD 33.9; P=.002). ConclusionsThe addition of personalized e-feedback in the enhanced program provided limited additional benefits compared to a standard commercial Web-based weight-loss program. However, it does support greater retention in the program and greater usage, which was related to weight loss. Further research is required to develop and examine Web-based features that may enhance engagement and outcomes and identify optimal usage patterns to enhance weight loss using Web-based programs. Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR) trial number: ACTRN12610000197033; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=335159 (Archived by WebCite at http://www.webcitation.org/6HoOMGb8j).

BackgroundInitial engagement and weight loss within Web-based weight loss programs may predict long-term success. The integration of persuasive Web-based features may boost engagement and therefore weight loss. ObjectiveTo determine whether an 8-week challenge within a commercial Web-based weight loss program influenced weight loss, website use, and attrition in the short term, when compared to the standard program. MethodsDe-identified data for participants (mean age 36.7±10.3 years; 86% female) who enrolled in the Biggest Loser Club (BLC) (n=952) and the BLC’s Shannan Ponton Fast Track Challenge (SC) for 8 weeks (n=381) were compared. The BLC program used standard evidence-based website features, with individualized calorie and exercise targets to facilitate a weight loss of 0.5-1 kg per week (–500kcal/day less than estimated energy expenditure). SC used the same website features but in addition promoted greater initial weight loss using a 1200 kcal/day energy intake target and physical activity energy expenditure of 600 kcal/day. SC used persuasive features to facilitate greater user engagement, including offering additional opportunities for social support (eg, webinar meetings with a celebrity personal trainer and social networking) endorsed by a celebrity personal trainer. Self-reported weekly weight records were used to determine weight change after 8 weeks. A primary analysis was undertaken using a generalized linear mixed model (GLMM) with all available weight records for all participants included. Dropout (participants who cancelled their subscription) and nonusage (participants who stopped using the Web-based features) attrition rates at 8 weeks were calculated. The number of participants who accessed each website feature and the total number of days each feature was used were calculated. The difference between attrition rates and website use for the two programs were tested using chi-square and Wilcoxon Rank Sum tests, respectively. ResultsUsing GLMM, including weight data for all participants, there was significantly greater (P=.03) 8-week weight loss in SC (–5.1 kg [–5.5 to –4.6 kg] or –6.0%) compared to BLC participants (–4.5 kg [–4.8, –4.2] or –5.0%). Dropout rates were low and consistent across groups (BLC: 17 (1.8%) vs SC: 2 (0.5%), P=.08) and 48.7% (456/936) of BLC and 51.2% (184/379) of SC participants accessed the website at 8 weeks, with no difference between programs (P=.48). SC participants accessed the discussion forums, menu plans, exercise plans, and educational materials significantly more than BLC participants (P

BackgroundThe development and use of Web-based programs for weight loss is increasing rapidly, yet they have rarely been evaluated using randomized controlled trials (RCTs). Interestingly, most people who attempt weight loss use commercially available programs, yet it is very uncommon for commercial programs to be evaluated independently or rigorously. ObjectiveTo compare the efficacy of a standard commercial Web-based weight-loss program (basic) versus an enhanced version of this Web program that provided additional personalized e-feedback and contact from the provider (enhanced) versus a wait-list control group (control) on weight outcomes in overweight and obese adults. MethodsThis purely Web-based trial using a closed online user group was an assessor-blinded RCT with participants randomly allocated to the basic or enhanced 12-week Web-based program, based on social cognitive theory, or the control, with body mass index (BMI) as the primary outcome. ResultsWe enrolled 309 adults (129/309, 41.8% male, BMI mean 32.3, SD 4 kg/m2) with 84.1% (260/309) retention at 12 weeks. Intention-to-treat analysis showed that both intervention groups reduced their BMI compared with the controls (basic: –0.72, SD 1.1 kg/m2, enhanced: –1.0, SD 1.4, control: 0.15, SD 0.82; P < .001) and lost significant weight (basic: –2.1, SD 3.3 kg, enhanced: –3.0, SD 4.1, control: 0.4, SD 2.3; P < .001) with changes in waist circumference (basic: –2.0, SD 3.5 cm, enhanced: –3.2, SD 4.7, control: 0.5, SD 3.0; P < .001) and waist-to-height ratio (basic: –0.01, SD 0.02, enhanced: –0.02, SD 0.03, control: 0.0, SD 0.02; P < .001), but no differences were observed between the basic and enhanced groups. The addition of personalized e-feedback and contact provided limited additional benefits compared with the basic program. ConclusionsA commercial Web-based weight-loss program can be efficacious across a range of weight-related outcomes and lifestyle behaviors and achieve clinically important weight loss. Although the provision of additional personalized feedback did not facilitate greater weight loss after 12 weeks, the impact of superior participant retention on longer-term outcomes requires further study. Further research is required to determine the optimal mix of program features that lead to the biggest treatment impact over time. Trial RegistrationAustralian New Zealand Clinical Trials Registry (ANZCTR): 12610000197033; http://www.anzctr.org.au/trial_view.aspx?id=335159 (Archived by WebCite at http://www.webcitation.org/66Wq0Yb7U)

BackgroundThere is a paucity of information in the scientific literature on the effectiveness of commercial weight loss programs, including Web-based programs. The potential of Web-based weight loss programs has been acknowledged, but their ability to achieve significant weight loss has not been proven. ObjectiveThe objectives were to evaluate the weight change achieved within a large cohort of individuals enrolled in a commercial Web-based weight loss program for 12 or 52 weeks and to describe participants’ program use in relation to weight change. MethodParticipants enrolled in an Australian commercial Web-based weight loss program from August 15, 2007, through May 31, 2008. Self-reported weekly weight records were used to determine weight change after 12- and 52-week subscriptions. The primary analysis estimated weight change using generalized linear mixed models (GLMMs) for all participants who subscribed for 12 weeks and also for those who subscribed for 52 weeks. A sensitivity analysis was conducted using the last observation carried forward (LOCF) method. Website use (ie, the number of days participants logged on, made food or exercise entries to the Web-based diary, or posted to the discussion forum) was described from program enrollment to 12 and 52 weeks, and differences in website use by percentage weight change category were tested using Kruskal-Wallis test for equality of populations. ResultsParticipants (n = 9599) had a mean (standard deviation [SD]) age of 35.7 (9.5) years and were predominantly female (86% or 8279/9599) and obese (61% or 5866/9599). Results from the primary GLMM analysis including all enrollees found the mean percentage weight change was −6.2% among 12-week subscribers (n = 6943) and −6.9% among 52-week subscribers (n = 2656). Sensitivity analysis using LOCF revealed an average weight change of −3.0% and −3.5% after 12 and 52 weeks respectively. The use of all website features increased significantly (P < .01) as percentage weight change improved. ConclusionsThe weight loss achieved by 12- and 52-week subscribers of a commercial Web-based weight loss program is likely to be in the range of the primary and sensitivity analysis results. While this suggests that, on average, clinically important weight loss may be achieved, further research is required to evaluate the efficacy of this commercial Web-based weight loss program prospectively using objective measures. The potential association between greater website use and increased weight loss also requires further evaluation, as strategies to improve participants’ use of Web-based program features may be required.

BackgroundAn understanding of the factors that predict retention and website use are critical to the development of effective Web-based weight loss interventions. However, poor retention (dropout attrition) and website utilization (nonusage attrition) are major inhibitors to the effectiveness of Web-based programs. ObjectiveThe study aimed to (1) describe the prevalence of dropout and nonusage attrition and (2) examine pretreatment predictors of nonusage attrition in a cohort of commercial Web-based weight loss program participants. MethodsParticipants enrolled in the online program, The Biggest Loser Club, Australia, from August 15, 2007, to May 31, 2008. Only those who subscribed for 12 or 52 weeks were included in this study. All data were collected by the program proprietors, SP Health Co Pty Ltd (Sydney, Australia), and provided in “deidentified” form. Data collected included responses to a pretreatment survey (sociodemographic and behavioral characteristics), subscription history (date of enrollment and subscription end), and website use (log-ins, food and exercise diary entries, weigh-ins, and forum posts). Participants were classified as a member of the program at 12 or 52 weeks if they held an active subscription plan at that point in time. Participants were classified as nonusers at 12 or 52 weeks if they had stopped using all of the website features and had not returned. Predictors of nonusage attrition were explored using Cox proportional hazards regression analysis. ResultsOf the 9599 eligible participants, 6943 (72%) subscribed to the program for 12 weeks, and 2656 (28%) subscribed for 52 weeks. Of all participants, 31% (2975/9599) were classified as overweight, 61% (5866/9599) were classified as obese, 86% (8279/9599) were female, and participants’ mean (SD) age was 35.7 (9.5) years. The 12 week and 52 week subscribers’ retention rates were 97% and 77% respectively. Of 12 week subscribers, 35% were classified as program “users” after 12 weeks, and 30% of 52 week subscribers were classified as “users” after 52 weeks. Significant predictors of nonusage attrition among 12 week subscribers included age (hazard ratio for 45 to 55 years of age = 0.83, 95% confidence interval [CI] 0.73 - 0.93, P = .001; hazard ratio for 55 to 65 years of age = 0.80, 95% CI 0.66 - 0.99, P = .04), exercise level (hazard ratio = 0.76, 95% CI 0.72 - 0.81, P < .001), emotional eating (hazard ratio = 1.11, 95% CI 1.04 - 1.18, P = .001), eating breakfast (hazard ratio = 0.88, 95% CI 0.82 - 0.95, P = .001), and skipping meals (hazard ratio = 1.12, 95% CI 1.04 -1.19, P = .001). For 52 week subscribers, eating breakfast (hazard ratio = 0.88, 95% CI 0.79 - 0.99, P = .04) and not drinking tea or coffee with sugar (hazard ratio = 1.23, 95% CI 1.11 - 1.37, P < .001) were the pretreatment characteristics that significantly decreased risk of nonusage attrition. ConclusionsThe findings demonstrate a high prevalence of nonusage attrition among a cohort of commercial Web-based weight loss program participants. Several sociodemographic and behavioral factors were shown to independently predict nonusage attrition.

Overweight and obesity prevalence in children has increased worldwide. One factor contributing to this rise is the increase in portion sizes, with individuals potentially having difficulties with portion size estimation. Portion size estimation could be improved with portion size education involving the mathematical concepts of volume and capacity. The current study aimed to explore mathematical teaching practices related to volume and capacity measurement in Australian primary schools, with a focus on use of nutrition related examples and technology. A convenience sample of 101 teachers completed an online exploratory survey reporting information on their teaching background, experience, use of resources, digital games and curricular integration. Results indicated that the teachers surveyed favoured use of Smartboards and cubes to teach volume and capacity, and the majority reported using nutrition-related examples including household measures, recipes and grocery shopping. They also expressed having positive beliefs and interest in using digital games for teaching these concepts. Although mathematics is most commonly integrated with science and technology, the teachers surveyed indicated that a digital game integrating nutrition and mathematics could be very useful. There is potential to investigate ways to integrate portion size estimation activities within mathematics teaching practices which can be facilitated using digital games.

Background/Objectives: Thus far, no studies have examined the relationship between fruit and vegetable (F and V) intake, urinary metabolite quantities, and weight change. Therefore, the aim of the current study was to explore changes in urinary metabolomic profiles during and after a 10-week weight loss intervention where participants were prescribed a high F and V diet (7 servings daily). Methods: Adults with overweight and obesity (n = 34) received medical nutrition therapy counselling to increase their F and V intakes to national targets (7 servings a day). Data collection included weight, dietary intake, and urine samples at baseline at week 2 and week 10. Urinary metabolite profiles were quantified using 1H NMR spectroscopy. Machine learning statistical approaches were employed to identify novel urine-based metabolite biomarkers associated with high F and V diet patterns at weeks 2 and 10. Metabolic changes appearing in urine in response to diet were quantified using Metabolite Set Enrichment Analysis (MSEA). Results: Energy intake was significantly lower (p = 0.02) at week 10 compared with baseline. Total F and V intake was significantly higher at week 2 and week 10 (p < 0.05). In total, 123 urinary metabolites were quantified. At week 10, 21 metabolites showed significant changes relative to baseline. Of these, 11 metabolites also significantly changed at week 2. These overlapping metabolites were acetic acid, dimethylamine, choline, fumaric acid, glutamic acid, L-tyrosine, histidine, succinic acid, uracil, histamine, and 2-hydroxyglutarate. Ridge Classifier and Linear Discriminant Analysis provided best prediction accuracy values of 0.96 when metabolite level of baseline was compared to week 10. Conclusions: Urinary metabolites quantified represent potential candidate biomarkers of high F and V intake, associated with a reduction in energy intake. Further studies are needed to validate these findings in larger population studies. [ABSTRACT FROM AUTHOR]

Aims The aim of this pilot randomised controlled trial (RCT) is to evaluate feasibility and acceptability of a personalised medical nutrition therapy (MNT) intervention on wound healing in individuals with diabetes-related foot ulceration (DFU) attending high risk foot clinics in New South Wales. It's hypothesised that the personalised MNT intervention will be more acceptable and will improve diet quality compared to standard care. Methods A six week superiority pilot multicentre, parallel-group two arm RCT for individuals (n=40) with type 1 and 2 diabetes, living with active DFU classified as VL or L as per WIfI grading and recruited from two-high risk foot clinics. The primary outcome is feasibility and acceptability, assessed by a process evaluation. The intervention group will receive MNT delivered by a dietitian at baseline, and weeks 2 and 4, with nutrient-dense food boxes provided at MNT consultations. The control group will receive a healthy eating brochure. Both groups received standardised podiatry care. Discussion The results from this pilot study will enhance understanding of feasibility and acceptabilty of MNT for those with DFU and its potential for impact on wound healing. Results will inform future fully powered RCTs investigating effectiveness of MNT in individuals with DFU. [ABSTRACT FROM AUTHOR]

Background The TRACE (Targeted Research for Addictive and Compulsive Eating) intervention was evaluated in a 3-month randomized controlled trial which demonstrated significant improvement in Yale Food Addiction Scale scores favoring dietitian-led telehealth (active intervention) compared with passive and control groups. This study aimed to determine intervention costs and cost-utility. Methods Costs of each intervention (2021$AUD) and incremental net monetary benefit (iNMB; incremental benefit, defined as Quality-Adjusted Life Years (QALY) gained, multiplied by willingness to pay threshold minus incremental cost) were calculated to estimate differences between groups. Results The active intervention (n = 38) cost $294 (95% UI: $266, $316) per person compared to $47 (95% UI: $40, $54) in the passive intervention (n = 24), and $26 in the control group (n = 37). At a cost-effectiveness threshold of $50 000 per QALY score gained, the active intervention iNMB was -$186 (95% UI: -$1137, $834) and the passive group $127 (95% UI: -$1137, $834). Compared to the control group, estimates indicate a 30% chance of the active intervention, and a 60% chance of the passive intervention being cost effective. Conclusion Although the overall cost of the active intervention was low, this was not considered cost-effective in comparison to the passive intervention, given small QALY score gains. Trial registration Australia New Zealand Clinical Trial Registry ACTRN12621001079831. [ABSTRACT FROM AUTHOR]

Background: Healthy dietary patterns can support the maintenance of cognition and brain health in older age and are negatively associated with cardiometabolic risk. Cardiometabolic risk factors are similarly important for cognition and may play an important role in linking diet to cognition. Aim: This study aimed to explore the relationship between dietary patterns and cognition and to determine whether cardiometabolic health markers moderate these relationships in older adulthood. Design: A cross-sectional analysis of observational data from the baseline of the ACTIVate study. Participants: The cohort included 426 cognitively normal adults aged 60–70 years. Methods: The Australian Eating Survey (AES) Food Frequency Questionnaire was used to collect data on usual dietary intake, along with additional questions assessing intake of dietary oils. Principal component analysis (PCA) was applied to reduce the dimensionality of dietary data. Cardiometabolic risk was quantified using the metabolic syndrome severity score (MetSSS). Tests from the Cambridge Neuropsychological Test Automated Battery (CANTAB) were used to derive composite scores on four cognitive domains: processing speed, executive function, short-term memory, and long-term memory. Results: Three dietary patterns were identified using PCA: a plant-dominant diet, a Western-style diet, and a meat-dominant diet. After controlling for age, sex, total years of education, energy intake, and moderate-to-vigorous physical activity (MVPA), there was a small, negative association between the meat-dominant diets and long-term memory. Subsequent moderation analysis indicated that MetSSS significantly moderated this relationship. Conclusions: Findings highlight the link between diet, cardiometabolic health, and cognitive function in older, cognitively healthy adults. However, longitudinal studies are needed to confirm observations and evaluate the dynamics of diet, cardiometabolic health, and cognitive function over time. [ABSTRACT FROM AUTHOR]

Emerging evidence suggests that nature imagery can affect consumer food choices. However, little is known about whether and, if so, how food companies use nature imagery as a means to appeal to consumers' environmental concerns as a marketing strategy. The current study aims to explore this matter for websites of Australian food companies. We extracted images from 45 Australian food company websites and coded for (1) nature type, (2) restorative effect, (3) level of cultivation and human interference, and (4) processing level (only for images with food present). All included food companies had a separate webpage dedicated to sustainability, and most nature images were located there. Sustainability pages had more images of 'pure nature' (i.e., no cultivation or human interference and high in restorative effects) and more 'urban' images compared to the main pages. Most food in the images was unprocessed, while only one image featured both nature and food. Australian food companies are commonly using images of nature on their sustainability webpages. The images might be used as a marketing strategy to connect with consumers' environmental concerns as a strategy to build trust and affinity with customers. However, companies currently do not combine nature imagery and their food products in one image on their websites. [ABSTRACT FROM AUTHOR]