Studying dietary intake in daily life through multilevel two-part modelling: a novel analytical approach and its practical application

Background Understanding which factors influence dietary intake, particularly in daily life, is crucial given the impact diet has on physical as well as mental health. However, a factor might influence whether but not how much an individual eats and vice versa or a factor’s importance may differ across these two facets. Distinguishing between these two facets, hence, studying dietary intake as a dual process is conceptually promising and not only allows further insights, but also solves a statistical issue. When assessing the association between a predictor (e.g. momentary affect) and subsequent dietary intake in daily life through ecological momentary assessment (EMA), the outcome variable (e.g. energy intake within a predefined time-interval) is semicontinuous. That is, one part is equal to zero (i.e. no dietary intake occurred) and the other contains right-skewed positive values (i.e. dietary intake occurred, but often only small amounts are consumed). However, linear multilevel modelling which is commonly used for EMA data to account for repeated measures within individuals cannot be applied to semicontinuous outcomes. A highly informative statistical approach for semicontinuous outcomes is multilevel two-part modelling which treats the outcome as generated by a dual process, combining a multilevel logistic/probit regression for zeros and a multilevel (generalized) linear regression for nonzero values. Methods A multilevel two-part model combining a multilevel logistic regression to predict whether an individual eats and a multilevel gamma regression to predict how much is eaten, if an individual eats, is proposed. Its general implementation in R, a widely used and freely available statistical software, using the R-package brms is described. To illustrate its practical application, the analytical approach is applied exemplary to data from the Eat2beNICE-APPetite-study. Results Results highlight that the proposed multilevel two-part model reveals process-specific associations which cannot be detected through traditional multilevel modelling. Conclusions This paper is the first to introduce multilevel two-part modelling as a novel analytical approach to study dietary intake in daily life. Studying dietary intake through multilevel two-part modelling is conceptually as well as methodologically promising. Findings can be translated to tailored nutritional interventions targeting either the occurrence or the amount of dietary intake

Studying microtemporal, within-person processes of diet, physical activity, and related factors using the appetite-mobile-app: Feasibility, usability, and validation study

Background: Diet and physical activity (PA) have a major impact on physical and mental health. However, there is a lack of effective strategies for sustaining these health-protective behaviors. A shift to a microtemporal, within-person approach is needed to capture dynamic processes underlying eating behavior and PA, as they change rapidly across minutes or hours and differ among individuals. However, a tool that captures these microtemporal, within-person processes in daily life is currently not present. Objective: The APPetite-mobile-app is developed for the ecological momentary assessment of microtemporal, within-person processes of complex dietary intake, objectively recorded PA, and related factors. This study aims to evaluate the feasibility and usability of the APPetite-mobile-app and the validity of the incorporated APPetite-food record. Methods: The APPetite-mobile-app captures dietary intake event-contingently through a food record, captures PA continuously through accelerometers, and captures related factors (eg, stress) signal-contingently through 8 prompts per day. Empirical data on feasibility (n=157), usability (n=84), and validity (n=44) were collected within the Eat2beNICE-APPetite-study. Feasibility and usability were examined in healthy participants and psychiatric patients. The relative validity of the APPetite-food record was assessed with a subgroup of healthy participants by using a counterbalanced crossover design. The reference method was a 24-hour recall. In addition, the energy intake was compared with the total energy expenditure estimated from accelerometry. Results: Good feasibility, with compliance rates above 80% for prompts and the accelerometer, as well as reasonable average response and recording durations (prompt: 2.04 min; food record per day: 17.66 min) and latencies (prompts: 3.16 min; food record: 58.35 min) were found. Usability was rated as moderate, with a score of 61.9 of 100 on the System Usability Scale. The evaluation of validity identified large differences in energy and macronutrient intake between the two methods at the group and individual levels. The APPetite-food record captured higher dietary intakes, indicating a lower level of underreporting, compared with the 24-hour recall. Energy intake was assessed fairly accurately by the APPetite-food record at the group level on 2 of 3 days when compared with total energy expenditure. The comparison with mean total energy expenditure (2417.8 kcal, SD 410) showed that the 24-hour recall (1909.2 kcal, SD 478.8) underestimated habitual energy intake to a larger degree than the APPetite-food record (2146.4 kcal, SD 574.5). Conclusions: The APPetite-mobile-app is a promising tool for capturing microtemporal, within-person processes of diet, PA, and related factors in real time or near real time and is, to the best of our knowledge, the first of its kind. First evidence supports the good feasibility and moderate usability of the APPetite-mobile-app and the validity of the APPetite-food record. Future findings in this context will build the foundation for the development of personalized lifestyle modification interventions, such as just-in-time adaptive interventions

Microtemporal Dynamics of Dietary Intake, Physical Activity, and Impulsivity in Adult Attention-Deficit/Hyperactivity Disorder: Ecological Momentary Assessment Study Within Nutritional Psychiatry

Background: Increasing attention is being paid to lifestyle factors, such as nutrition and physical activity (PA), as potential complementary treatment options in attention-deficit/hyperactivity disorder (ADHD). Previous research indicates that sugar and saturated fat intake may be linked to increased impulsivity, a core symptom of ADHD, whereas protein intake and PA may be related to reduced impulsivity. However, most studies rely on cross-sectional data that lack microtemporal resolution and ecological validity, wherefore questions of microtemporal dynamics (eg, is the consumption of foods high in sugar associated with increased impulsivity within minutes or hours?) remain largely unanswered. Ecological momentary assessment (EMA) has the potential to bridge this gap. Objective: This study is the first to apply EMA to assess microtemporal associations among macronutrient intake, PA, and state impulsivity in the daily life of adults with and without ADHD. Methods: Over a 3-day period, participants reported state impulsivity 8 times per day (signal-contingent), recorded food and drink intake (event-contingent), and wore an accelerometer. Multilevel 2-part models were used to study the association among macronutrient intake, PA, and the probability to be impulsive as well as the intensity of impulsivity (ADHD: n=36; control: n=137). Results: No association between macronutrient intake and state impulsivity was found. PA was not related to the intensity of impulsivity but to a higher probability to be impulsive (ADHD: β=−.09, 95% CI −0.14 to −0.04; control: β=−.03, 95% CI −0.05 to −0.01). No evidence was found that the combined intake of saturated fat and sugar amplified the increase in state impulsivity and that PA alleviated the positive association between sugar or fat intake and state impulsivity. Conclusions: Important methodological considerations are discussed that can contribute to the optimization of future EMA protocols. EMA research in the emerging field of nutritional psychiatry is still in its infancy; however, EMA is a highly promising and innovative approach as it offers insights into the microtemporal dynamics of psychiatric symptomology, dietary intake, and PA in daily life

Individual differences in the dietary response to stress in ecological momentary assessment: Does the individual‐difference model need expansion?

According to the individual-difference model, individuals differ in the way stress changes their eating behaviour. Research shows that some increase, some decrease, and others show no change in food intake. Despite numerous efforts to identify moderating variables that explain these individual (i.e., between-person) differences, evidence remains inconclusive. The present study aims at deepening the understanding of the stress and eating relationship by applying ecological momentary assessment to study (1) the influence of stress on whether and how much individuals eat and (2) the moderating role of gender, age, BMI, trait stress-eating, and eating styles. The APPetite-mobile-app was used for 3 days to capture actual food intake (event-contingent) and perceived stress (signal-contingent). Data of 154 healthy adults suggest that stress is not associated with whether but how much individuals eat. Only gender moderated the relationship between stress and the amount of food intake. Individual differences were small indicating that an individual\u27s dietary response to stress might not be as stable as yet assumed. Moreover, a study suggests that time-varying factors (e.g., food availability) moderate the stress and eating relationship. Hence, intraindividual (i.e., within-person) variability may be relevant. Therefore, we propose an expansion of the individual-difference model, which accounts for time-varying factors

Stress and food intake in daily life : insights based on a novel ecological momentary assessment tool and an advanced data analysis approach

Stress influences health not only directly, but also indirectly through changes in health-related behaviours, such as diet. Research has shown that stress influences individuals’ eating behaviour in different ways: Some increase, some decrease food intake, while others show no change. Identifying individuals at risk for stress-induced eating is essential for the development of tailored strategies for the prevention and treatment of overweight and obesity. The individual-difference model of stress-induced eating suggests that individual differences in the dietary response to stress are determined by differences in learning history, attitudes, or biology. Even though many studies have tried to identify person-characteristics that explain individual differences in the dietary response to stress, evidence remains inconclusive. Considering that eating is a repeated-occurrence health behaviour which is performed multiple times a day, Ecological Momentary Assessment (EMA) seems particularly promising to study the complex relationship between stress and food intake when and where it naturally occurs. Despite its potential, the number of studies applying EMA to assess the stress and eating relationship is limited. Furthermore, previous EMA studies show two limitations: (1) Actual food intake is not assessed and (2) inappropriate data analysis approaches are applied to semicontinuous outcomes. Therefore, the first aim of the present dissertation was to address the lack of an EMA tool that allows the assessment of stress and actual food intake by developing and evaluating the APPetite-mobile-app. Feasibility and usability of the APPetite-mobile-app as well as validity of the incorporated food record were empirically examined (Paper 1). Given the lack of an appropriate data analysis procedure, the second aim of the present dissertation was the introduction of a sophisticated statistical approach for semicontinuous data (Paper 2): Multilevel two-part modelling allows studying the influence of stress on the occurrence (i.e., whether individuals eat) as well as the amount of food intake (i.e., how much individuals eat) while accounting for the potential dependency between the two. Lastly, the novel EMA tool and the advanced data analysis procedure were integrated in order to gain novel insights into individual differences in the dietary response to stress and thereby identify individuals at risk for stress-induced eating in daily life (Paper 3). Results of Paper 1 showed good feasibility and acceptable usability of the APPetite-mobile-app as well as validity of the incorporated food record. Findings of Paper 2 highlight that multilevel two-part models offer novel and distinct insights in terms of the occurrence and the amount of food intake and are therefore not only methodologically but also conceptually promising. Paper 3 provides first evidence that the dietary response to stress might not be as stable as yet assumed. Time-varying factors might moderate the relationship between stress and actual food intake. Therefore, an expansion of the individual-difference model is proposed which accounts for time-varying factors. Further EMA studies are needed to verify the expanded model and identify time-varying factors which influence the dietary response to stress. Beyond that, improvements in the dietary assessment are required in order to allow prolonged EMA periods as well as larger samples. The present dissertation contributes to the research on the stress and eating relationship as it overcomes limitations of previous EMA studies and yields novel insights into the relationship between stress and actual food intake in daily life. Not only identifying individuals at risk for stress-induced eating, but also the identification of situations with an increased risk for stress-induced eating appears to be important for the development of targeted strategies for the prevention and treatment of overweight and obesity.Sowohl die Ernährung als auch das Stressempfinden haben einen direkten Einfluss auf die menschliche Gesundheit. Darüber hinaus beeinflusst Stress die Gesundheit indirekt durch Veränderungen von Gesundheitsverhalten, wie zum Beispiel der Ernährung. Studien konnten zeigen, dass sich Personen hinsichtlich ihrer Nahrungsaufnahme bei Stress unterscheiden: Manche essen mehr, manche weniger, während andere keine Veränderung zeigen. Das “individual-difference model” von Greeno und Wing (1994) besagt, dass Unterschiede in der Nahrungsaufnahme bei Stress auf individuelle Unterschiede in der Lerngeschichte, den Einstellungen oder der Biologie zurückzuführen sind. Die Identifikation von Personen mit erhöhtem Risiko für stressbedingte Nahrungsaufnahme ist demnach von entscheidender Bedeutung für die Entwicklung gezielter Maßnahmen zur Prävention und Behandlung von Übergewicht und Adipositas. Basierend darauf verfolgten zahlreiche Studien das Ziel, Personenmerkmale zu identifizieren, die individuelle Unterschiede in der Nahrungsaufnahme bei Stress erklären. Es zeigten sich jedoch widersprüchliche Befunde. Eine Metaanalyse von Hill et al. aus dem Jahr 2021 fand keine studienübergreifenden Hinweise darauf, dass Geschlecht, Alter, Gewichtsstatus und Essstil den Zusammenhang zwischen Stress und der Nahrungsaufnahme moderieren. Die Autoren weisen jedoch darauf hin, dass sich eine große Zahl der einbezogenen Studien entweder auf lediglich einen einzelnen Aspekt des Essverhaltens (z. B. Snacks zwischen den Mahlzeiten) beschränkte oder die Nahrungsaufnahme in einer künstlichen Umgebung (d. h. im Labor) untersuchte. Im Gegensatz dazu ermöglicht es der Ansatz des Ecological Momentary Assessments (EMA), die Beziehung zwischen Stress und der Nahrungsaufnahme im Alltag, unmittelbar wo und wann sie sich auf natürliche Weise zeigt, zu untersuchen. EMA beinhaltet die wiederholte Erfassung von Verhalten (z. B. Nahrungsaufnahme), Erfahrungen (z. B. Stress) und/oder physiologischen Parametern innerhalb eines Tages über mehrere Tage hinweg im Alltag. Hierdurch wird die Untersuchung komplexer psychologischer, verhaltensbezogener und/oder physiologischer Prozesse im Alltag ermöglicht (Smyth & Stone, 2003). Darüber hinaus erlaubt EMA es, enge zeitliche Zusammenhänge zwischen Stress und der Nahrungsaufnahme über Minuten und Stunden hinweg zu untersuchen. Obwohl EMA einen vielversprechenden Ansatz für die Untersuchung des Zusammenhangs von Stress und der Nahrungsaufnahme im Alltag darstellt, wurde es bislang in nur wenigen Studien genutzt. Bisherige EMA-Studien weisen zudem zwei Limitationen auf: (1) Sie erfassen die Nahrungsaufnahme lediglich mittels subjektiver Selbsteinschätzung, z. B. von 0 – zu wenig gegessen bis 100 – zu viel gegessen (Reichenberger et al., 2021), oder erfassen ausschließlich einzelne Aspekte der Nahrungsaufnahme, z. B. den Konsum von Snacks (Zenk et al., 2014). So untersucht bislang keine Studie den Zusammenhang von Stress und der tatsächlichen Nahrungsaufnahme in einer gesunden Stichprobe mittels EMA. Die tatsächliche Nahrungsaufnahme bezieht sich auf die Erfassung aller verzehrten Lebensmittel und Getränke sowie der verzehrten Mengen, die nachfolgend zur Ermittlung von Nährwerten (z. B. Energie und Makronährstoffe) verwendet werden. (2) EMA ermöglicht es, zu untersuchen, ob das Stressempfinden, welches mehrmals am Tag erfasst wird, mit der Nahrungsaufnahme innerhalb eines festgelegten Zeitintervalls (z. B. innerhalb der nächsten Stunde) assoziiert ist. In der Regel erfolgt jedoch nicht in jedem dieser Zeitintervalle eine Nahrungsaufnahme oder es werden nur geringe Mengen (z. B. ein Snack) verzehrt. Infolgedessen ergibt sich eine Kriteriumsvariable, die zahlreiche Nullen sowie rechtsschiefe positive Werte enthält. Diese Art von Variablen wird häufig als semikontinuierlich bezeichnet und kann nicht mittels traditioneller linearer Mehrebenenmodelle analysiert werden, da die Annahme normalverteilter Residuen mit großer Wahrscheinlichkeit verletzt ist. Bisherige EMA-Studien nutzten für die Analyse der semikontinuierlichen Kriteriumsvariable ungeeignete statistische Verfahren, die sich entweder auf den Einfluss von Stress auf das Auftreten von Nahrungsaufnahme, d. h. ob gegessen wird (z. B. Zenk et al., 2014), oder auf die Menge der Nahrungsaufnahme, d. h. wie viel gegessen wird (z. B. Reichenberger et al., 2021), beschränken. Beide Analyseansätze sind jedoch mit Informationsverlust verbunden. Basierend auf den Limitationen bisheriger EMA-Studien bedarf es (1) eines EMA-Instruments, das die Erfassung von Stress und tatsächlicher Nahrungsaufnahme erlaubt, sowie (2) eines statistischen Verfahrens, das die semikontinuierliche Kriteriumsvariable angemessen berücksichtigt. Nur so kann das Verständnis der Beziehung zwischen Stress und der Nahrungsaufnahme im Alltag vertieft und Personen mit erhöhtem Risiko für stressbedingte Nahrungsaufnahme im Alltag identifiziert werden

Association between diet and impulsivity in ADHD – results of the Eat2beNice-APPetite study

Introduction: The influence of our diet on mental health is of increasing importance in current research. Study results on the gut-brain axis suggest that the gut microbiome can influence mental processes via neuronal, hormonal and immune signaling pathways [1]. The gut microbiome is largely influenced by our diet. Some studies provide evidence that a "Western diet" rich in saturated fat and sugar may promote mental disorders [2]. There is evidence, that dietary behaviour in individuals with Attention Deficit Hyperactivity Disorder (ADHD) is characterized by an increased intake of sugar and saturated fat [3]. So far, it is unclear whether this dietary pattern contributes to ADHD symptoms such as impulsivity. The aim of this study is to investigate the influence of certain macronutrients such as fats and mono/disaccharides on impulsivity in individuals with ADHD. Using our APPetite-mobile-app [4] enabled us to study dietary behaviour and momentary impulsiveness in everyday life of our participants. Methods: 43 participants with ADHD (mean age 36.0 ± 12.3 years, 21 females) and 186 healthy controls (mean age 28.5 ± 7.7 years, 133 females) without any psychiatric condition were included into the study. Food intake was recorded over a period of three days using the APPetite-mobile-app via a 6 step process: (1) Selection of meal type, (2) Entry of time of meal, (3) Selection of consumed foods and drinks, (4) Specification of consumed amounts, (5) Presentation of reminder for commonly forgotten foods, and (6) Indication of predominant reason for eating. In addition to entering consumed foods in the APPetite-mobile-app, subjects completed an online food log for the last 24 hours (myfood 24) at the beginning of the study. After the data collection period, a detailed analysis of the ingested nutrients was performed for each subject. Trait impulsivity was assessed using the UPPS-P, a self-assessment questionnaire. Momentary impulsiveness was assessed via the mHealth APP by means of the Momentary Impulsiveness scale (MIS). The MIS consists of 4 questions capturing different aspects of impulsivity. The participants were prompted to answer these questions at 8 semi-random times per day between 8 AM and 10 PM. The minimum time between 2 prompts was 1 hour. Thereby participants could not predict the exact time of the next prompt and the assessed situations are a better reflection of the participant’s real life. Results: ANOVA revealed higher levels of both, trait and momentary impulsivity in individuals with ADHD compared to controls (p < 0,01). After preprocessing of data that was sampled via the mHealth APP is completed, a regression analysis with different macronutrients as predictors and impulsivity as dependent variable will be computed. To assess the association between momentary impulsiveness and dietary intake, generalized linear multilevel modelling will be used. Results of these analyses will be presented

Studying microtemporal, within-person processes of diet, physical activity, and related factors using the APPetite-mobile-app: feasibility, usability, and validation study

Background: Diet and physical activity (PA) have a major impact on physical and mental health. However, there is a lack of effective strategies for sustaining these health-protective behaviors. A shift to a microtemporal, within-person approach is needed to capture dynamic processes underlying eating behavior and PA, as they change rapidly across minutes or hours and differ among individuals. However, a tool that captures these microtemporal, within-person processes in daily life is currently not present. Objective: The APPetite-mobile-app is developed for the ecological momentary assessment of microtemporal, within-person processes of complex dietary intake, objectively recorded PA, and related factors. This study aims to evaluate the feasibility and usability of the APPetite-mobile-app and the validity of the incorporated APPetite-food record. Methods: The APPetite-mobile-app captures dietary intake event-contingently through a food record, captures PA continuously through accelerometers, and captures related factors (eg, stress) signal-contingently through 8 prompts per day. Empirical data on feasibility (n=157), usability (n=84), and validity (n=44) were collected within the Eat2beNICE-APPetite-study. Feasibility and usability were examined in healthy participants and psychiatric patients. The relative validity of the APPetite-food record was assessed with a subgroup of healthy participants by using a counterbalanced crossover design. The reference method was a 24-hour recall. In addition, the energy intake was compared with the total energy expenditure estimated from accelerometry. Results: Good feasibility, with compliance rates above 80% for prompts and the accelerometer, as well as reasonable average response and recording durations (prompt: 2.04 min; food record per day: 17.66 min) and latencies (prompts: 3.16 min; food record: 58.35 min) were found. Usability was rated as moderate, with a score of 61.9 of 100 on the System Usability Scale. The evaluation of validity identified large differences in energy and macronutrient intake between the two methods at the group and individual levels. The APPetite-food record captured higher dietary intakes, indicating a lower level of underreporting, compared with the 24-hour recall. Energy intake was assessed fairly accurately by the APPetite-food record at the group level on 2 of 3 days when compared with total energy expenditure. The comparison with mean total energy expenditure (2417.8 kcal, SD 410) showed that the 24-hour recall (1909.2 kcal, SD 478.8) underestimated habitual energy intake to a larger degree than the APPetite-food record (2146.4 kcal, SD 574.5). Conclusions: The APPetite-mobile-app is a promising tool for capturing microtemporal, within-person processes of diet, PA, and related factors in real time or near real time and is, to the best of our knowledge, the first of its kind. First evidence supports the good feasibility and moderate usability of the APPetite-mobile-app and the validity of the APPetite-food record. Future findings in this context will build the foundation for the development of personalized lifestyle modification interventions, such as just-in-time adaptive interventions

Exploring the link between lifestyle, inflammation, and insulin resistance through an improved healthy living index

Lifestyle factors—such as diet, physical activity (PA), smoking, and alcohol consumption—have a significant impact on mortality as well as healthcare costs. Moreover, they play a crucial role in the development of type 2 diabetes mellitus (DM2). There also seems to be a link between lifestyle behaviours and insulin resistance, which is often a precursor of DM2. This study uses an enhanced Healthy Living Index (HLI) integrating accelerometric data and an Ecological Momentary Assessment (EMA) to explore differences in lifestyle between insulin-sensitive (IS) and insulin-resistant (IR) individuals. Moreover, it explores the association between lifestyle behaviours and inflammation. Analysing data from 99 participants of the mPRIME study (57 women and 42 men; mean age 49.8 years), we calculated HLI scores—ranging from 0 to 4— based on adherence to specific low-risk lifestyle behaviours, including non-smoking, adhering to a healthy diet, maximally moderate alcohol consumption, and meeting World Health Organization (WHO) PA guidelines. Insulin sensitivity was assessed using a Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) levels were used as a proxy for inflammation. Lifestyle behaviours, represented by HLI scores, were significantly different between IS and IR individuals (U = 1529.0; p = 0.023). The difference in the HLI score between IR and IS individuals was mainly driven by lower adherence to PA recommendations in the IR group. Moreover, reduced PA was linked to increased CRP levels in the IR group (r = −0.368, p = 0.014). Our findings suggest that enhancing PA, especially among individuals with impaired insulin resistance, holds significant promise as a preventive strategy

Microtemporal Dynamics of Dietary Intake, Physical Activity, and Impulsivity in Adult Attention-Deficit/Hyperactivity Disorder: Ecological Momentary Assessment Study Within Nutritional Psychiatry

BackgroundIncreasing attention is being paid to lifestyle factors, such as nutrition and physical activity (PA), as potential complementary treatment options in attention-deficit/hyperactivity disorder (ADHD). Previous research indicates that sugar and saturated fat intake may be linked to increased impulsivity, a core symptom of ADHD, whereas protein intake and PA may be related to reduced impulsivity. However, most studies rely on cross-sectional data that lack microtemporal resolution and ecological validity, wherefore questions of microtemporal dynamics (eg, is the consumption of foods high in sugar associated with increased impulsivity within minutes or hours?) remain largely unanswered. Ecological momentary assessment (EMA) has the potential to bridge this gap. ObjectiveThis study is the first to apply EMA to assess microtemporal associations among macronutrient intake, PA, and state impulsivity in the daily life of adults with and without ADHD. MethodsOver a 3-day period, participants reported state impulsivity 8 times per day (signal-contingent), recorded food and drink intake (event-contingent), and wore an accelerometer. Multilevel 2-part models were used to study the association among macronutrient intake, PA, and the probability to be impulsive as well as the intensity of impulsivity (ADHD: n=36; control: n=137). ResultsNo association between macronutrient intake and state impulsivity was found. PA was not related to the intensity of impulsivity but to a higher probability to be impulsive (ADHD: β=−.09, 95% CI −0.14 to −0.04; control: β=−.03, 95% CI −0.05 to −0.01). No evidence was found that the combined intake of saturated fat and sugar amplified the increase in state impulsivity and that PA alleviated the positive association between sugar or fat intake and state impulsivity. ConclusionsImportant methodological considerations are discussed that can contribute to the optimization of future EMA protocols. EMA research in the emerging field of nutritional psychiatry is still in its infancy; however, EMA is a highly promising and innovative approach as it offers insights into the microtemporal dynamics of psychiatric symptomology, dietary intake, and PA in daily life