title: Exploring individual and environmental determinants of food intake
Creators: name: Elliston, KG
Publisher: name: University of Tasmania
Year: 2021

description: Rates of overweight and obesity have increased worldwide over the past 30 years. This has directly led to an increase in health conditions such as hypertension, type 2 diabetes, heart disease and stroke. These health conditions pose significant risk to the individual and a huge financial burden on the community, making the need for evidence-based weight-control measures vital. Weight gain is ultimately driven by excess energy intake and insufficient energy expenditure. One of the key behavioural determinants of this energy imbalance is discretionary food intake. Discretionary foods commonly referred to as “snacks”, are non-essential foods consumed outside of main meals. These foods are typically energydense and nutritionally-poor, and have been estimated to contribute, on average, one third of an individual’s daily energy intake. The consumption of discretionary foods is believed to be driven by both motivated, intentional decisions (i.e., people making the decision to snack or not), and momentary (variable) factors within the environment. The interaction between motivational and momentary eating cues is important. However, previous research on eating has either focused on motivated behavioural goals or on lab-based manipulations of food cues, thereby missing the fluctuating environmental exposures that prompt food intake. The studies in this thesis use Ecological Momentary Assessment (EMA) methods to examine the determinants of discretionary food intake. Through the use of EMA, individuals are studied in naturalistic environments as they go about their daily lives, thereby improving ecological validity and allowing for examination of contextual cues related to eating. This, in conjunction with baseline assessments of individuals’ dietary motivations, enable a greater understanding of the determinants of discretionary food intake. Four complimentary studies were conducted with the aim to better understand the individual and contextual determinants of discretionary food intake. This thesis begins by examining how individuals prioritise and manage their dietary goals with other personal goals (Study 1, Chapter 2). In this study, dieters recorded their food and drink intake in real-time and provided a summary of engagement with their personal goals at the end of each day. The findings suggest that although daily food intake predicted long-term weight-loss, motivational determinants such as dieting goals and individuals’ intentions may not be particularly important in guiding real-time eating decisions. Contextual factors need to be examined to better understand the how eating decisions are made in the moments leading up to food intake. Study 2 (Chapter 3) examined discretionary food intake from an integrated perspective, using Temporal Self-Regulation Theory. Here, the interplay between individual motivations (i.e., self-regulatory capacity and behaviour pre-potency) and momentary cues (i.e., seeing others eat, experiencing negative affect and having food available) in shaping health behaviour self-regulation were explored. In this study, participants completed a baseline assessment of the motivations towards healthy eating and recorded their food intake in real-time using EMA methods. The findings showed discretionary food intake is largely guided by momentary cues, and motivational-level factors are less important in the initiation of discretionary food consumption. Given this finding, dietary interventions should aim to target the momentary cues which are associated with discretionary food intake. Study 3 (Chapter 4) further examines the momentary cues guiding eating. Cues such as negative affect, the presence and availability of food and the presence of others eating were explored. Study 3 focused specifically on the momentary food environment shaping real-time eating decisions among people with overweight and obesity. Participants reported their food intake and exposure to environmental cues using EMA 14 methods. The findings suggest contextual cues are associated with both main meal and discretionary food intake, and perceptions of the food environment influence food choice. Therefore, dietary interventions should combine individuals’ healthy eating intentions and momentary cues with environmental-level interventions targeting the placement of food outlets. Study 4 (Chapter 5) built on the results from Chapter 4 to examine discretionary food intake from the influence of the community nutrition environment. In this study, participants recorded their food intake and reported on the number and type of food outlets nearby in-real time using an EMA approach. Alongside participants reports, their electronic diaries recorded their GPS coordinates. GPS coordinates were overlaid onto a map of food outlets to produce an objective count of the number of food outlets surrounding an individual. Although further research is needed, the results suggest that subjective reports of the food environment predict eating better than objectively measured food environments. This is an important finding, as it suggests mHealth apps offering dietary advice may need to consider the type of food outlets rather than the raw number of food outlets near an individual. Chapter 6 explores the common determinants and consequences of snacking and how we can best apply interventions to modify discretionary food intake. Across the research in this thesis, momentary factors were more predictive of discretionary food intake than motivational-level factors, highlighting the need for dietary interventions to address the environments that people consume food in. Momentary cue interventions include mHealth apps which can tailor dietary information based on an individual’s location. The first two studies in this thesis expand the knowledge on motivational cues of eating by examining how personal goals and self-regulatory ability are associated with food intake. Additionally, by investigating contextual cues through both self-report (Chapter 4) and passively-collected GPS data (Chapter 5), new targets for mHealth dietary interventions are developed. Overall, the studies demonstrate how individual-level motivations and momentary factors within the immediate environment prompt real-time eating decisions, ultimately generating an evidence-based direction for dietary interventions aimed at reducing the burden of overweight and obesity and associated health conditions.