There are limited methods to assess how dietary patterns adhere to a healthy and sustainable diet. The aim of this study was to develop a theoretically derived Healthy and Sustainable Diet Index (HSDI). The HSDI uses 12 components within five categories related to environmental sustainability: animal-based foods, seasonal fruits and vegetables, ultra-processed energy-dense nutrient-poor foods, packaged foods and food waste. A maximum of 90 points indicates the highest adherence. The HSDI was applied to 4-day mobile food records (mFRTM) from 247 adults (18−30 years). The mean HSDI score was 42.7 (SD 9.3). Participants who ate meat were less likely to eat vegetables (p < 0.001) and those who ate non-animal protein foods were more likely to eat more fruit (p < 0.001), vegetables (p < 0.05), and milk, yoghurt and cheese (p < 0.05). After adjusting for age, sex and body mass index, multivariable regression found the strongest predictor of the likelihood of being in the lowest total HSDI score tertile were people who only took a bit of notice [OR (95%CI) 5.276 (1.775, 15.681) p < 0.005] or did not pay much/any attention to the health aspects of their diet [OR (95%CI) 8.308 (2.572, 26.836) p < 0.0001]. HSDI provides a new reference standard to assess adherence to a healthy and sustainable diet.
Improving dietary reporting among people living with obesity is challenging as many factors influence reporting accuracy. Reactive reporting may occur in response to dietary recording but little is known about how image-based methods influence this process. Using a 4-day image-based mobile food record (mFRTM), this study aimed to identify demographic and psychosocial correlates of measurement error and reactivity bias, among adults with BMI 25-40kg/m2. Participants (n=155, aged 18-65y) completed psychosocial questionnaires, and kept a 4-day mFRTM. Energy expenditure (EE) was estimated using ≥4 days of hip-worn accelerometer data, and energy intake (EI) was measured using mFRTM. Energy intake: energy expenditure ratios were calculated, and participants in the highest tertile were considered to have Plausible Intakes. Negative changes in EI according to regression slopes indicated Reactive Reporting. Mean EI was 72% (SD=21) of estimated EE. Among participants with Plausible Intakes, mean EI was 96% (SD=13) of estimated EE. Higher BMI (OR 0.81, 95%CI 0.72-0.92) and greater need for social approval (OR 0.31, 95% CI 0.10-0.96), were associated with lower likelihood of Plausible Intakes. Estimated EI decreased by 3% per day of recording (IQR -14%,6%) among all participants. The EI of Reactive Reporters (n=52) decreased by 17%/day (IQR -23%,-13%). A history of weight loss (>10kg) (OR 3.4, 95% CI 1.5-7.8), and higher percentage of daily energy from protein (OR 1.1, 95%CI 1.0-1.2) were associated with greater odds of Reactive Reporting. Identification of reactivity to measurement, as well as Plausible Intakes, is recommended in community-dwelling studies to highlight and address sources of bias.