Dietary Intake Assessment: From Traditional Paper-Pencil Questionnaires to Technology-Based Tools

The role of perceived negative partner behavior in daily snacking behavior: A dynamical systems approach

Past work suggested that psychological stress, especially in the context of relationship stress, is associated with increased consumption of energy-dense food and when maintained for long periods of time, leads to adverse health consequences. Furthermore, this association is moderated by a variety of factors, including emotional over-eating style. That being said, few work utilized a dynamical system approach to understand the intraindividual and interindividual fluctuations within this process. The current study utilized a 14-day daily diary study, collected between January-March 2020, where participants reported their partner's negative relationship behavior and their own snacking behavior. A differential equation model was applied to the daily dairy data collected. Results showed that snacking behavior followed an undamped oscillator model while negative relationship behavior followed a damped coupled oscillator model. In other words, snacking behavior fluctuated around an equilibrium but was not coupled within dyadic partners. Negative relationship behavior fluctuated around an equilibrium and was amplified over time, coupled within dyadic partners. Furthermore, we found a two-fold association between negative relationship behavior and snacking: while the association between the displacement of negative relationship behavior and snacking was negative, change in negative relationship behavior and snacking were aligned. Thus, at any given time, one's snacking depends both on the amount of negative relationship behaviors one perceives and the dynamical state a dyad is engaging in (i.e., whether the negative relationship behavior is "exacerbating" or "resolving"). This former association was moderated by emotional over-eating style and the latter association was not. The current findings highlight the importance of examining dynamics within dyadic system and offers empirical and methodological insights for research in adult relationships.

User Requirements in Developing a Novel Dietary Assessment Tool for Children: Mixed Methods Study

BACKGROUND

The prevalence of childhood obesity and comorbidities is rising alarmingly, and diet is an important modifiable determinant. Numerous dietary interventions in children have been developed to reduce childhood obesity and overweight rates, but their long-term effects are unsatisfactory. Stakeholders call for more personalized approaches, which require detailed dietary intake data. In the case of primary school children, caregivers are key to providing such dietary information. However, as school-aged children are not under the full supervision of one specific caregiver anymore, data are likely to be biased. Recent technological advancements provide opportunities for the role of children themselves, which would serve the overall quality of the obtained dietary data.

OBJECTIVE

This study aims to conduct a child-centered exploratory sequential mixed methods study to identify user requirements for a dietary assessment tool for children aged 5 to 6 years.

METHODS

Formative, nonsystematic narrative literature research was undertaken to delineate initial user requirements and inform prototype ideation in an expert panel workshop (n=11). This yielded 3 prototype dietary assessment tools: FoodBear (tangible piggy bank), myBear (smartphone or tablet app), and FoodCam (physical camera). All 3 prototypes were tested for usability by means of a usability task (video analyses) and user experience (This or That method) among 14 Dutch children aged 5 to 6 years (n=8, 57% boys and n=6, 43% girls).

RESULTS

Most children were able to complete FoodBear's (11/14, 79%), myBear's (10/14, 71%), and FoodCam's (9/14, 64%) usability tasks, but all children required assistance (14/14, 100%) and most of the children encountered usability problems (13/14, 93%). Usability issues were related to food group categorization and recognition, frustrations owing to unsatisfactory functioning of (parts) of the prototypes, recall of food products, and the distinction between eating moments. No short-term differences in product preference between the 3 prototypes were observed, but autonomy, challenge, gaming elements, being tablet based, appearance, social elements, and time frame were identified as determinants of liking the product.

CONCLUSIONS

Our results suggest that children can play a complementary role in dietary data collection to enhance the data collected by their parents. Incorporation of a training program, auditory or visual prompts, reminders and feedback, a user-friendly and intuitive interaction design, child-friendly food groups or icons, and room for children's autonomy were identified as requirements for the future development of a novel and usable dietary assessment tool for children aged 5 to 6 years. Our findings can serve as valuable guidance for ongoing innovations in the field of children's dietary assessment and the provision of personalized dietary support.

Adherence to a lifestyle monitoring system in patients with heart disease: protocol for the care-on prospective observational trial

BACKGROUND

Lifestyle factors such as physical fitness, dietary habits, mental stress, and sleep quality, are strong predictors of the occurrence, clinical course, and overall treatment outcomes of common cardiovascular diseases. However, these lifestyle factors are rarely monitored, nor used in daily clinical practice and personalized cardiac care. Moreover, non-adherence to long-term self-reporting of these lifestyle factors is common. In the present study, we evaluate adherence to a continuous unobtrusive and patient-friendly lifestyle monitoring system using evidence-based assessment tools.

METHODS

In a prospective observational trial (N = 100), the project investigates usability of and adherence to a monitoring system for multiple lifestyle factors relevant to cardiovascular disease, i.e., daily physical activity levels, dietary habits, mental stress, smoking, and sleep quality. Patients with coronary artery disease, valvular disease and arrhythmias undergoing an elective intervention are asked to participate. The monitoring system consists of a secured online platform with a custom-built conversational interface-a chatbot-and a wrist-worn wearable medical device. The wrist-worn device collects continuous objective data on physical activity and the chatbot is used to collect self-report data. Participants collect self-reported lifestyle data via the chatbot for a maximum of 4 days every other week; in the same week physiological data are collected for 7 days for 24 h. Data collection starts one week before the intervention and continues until 1-year after discharge. Via a dashboard, patients can observe their lifestyle measures and adherence to self-reporting, set and track personal goals, and share their lifestyle data with practitioners and relatives. The primary outcome of the trial is adherence to using the integrated platform for self-tracking data. The secondary outcomes include system usability, determinants of adherence and the relation between baseline lifestyle behaviour and long-term patient-relevant outcomes.

DISCUSSION

Systematic monitoring during daily life is essential to gain insights into patients' lifestyle behaviour. In this context, adherence to monitoring systems is critical for cardiologists and other care providers to monitor recovery after a cardiac intervention and to detect clinical deterioration. With this project, we will evaluate patients' adherence to lifestyle monitoring technology. This work contributes to the understanding of patient-centered data collection and interpretation, to enable personalized care after cardiac interventions in order to ultimately improve patient-relevant outcomes and reduce health care costs.

TRIAL REGISTRATION

Netherlands Trial Registry (NTR) NL9861. Registered 6th of November 2021.

Validation of the smartphone-based dietary assessment tool 'Traqq' for assessing actual dietary intake by repeated 2-hour recalls in adults: comparison with 24h recalls and urinary biomarkers

BACKGROUND

Conventional dietary assessment methods are affected by measurement error. We developed a smartphone-based 2-hour recall (2hR) methodology to reduce participant burden and memory-related bias.

OBJECTIVE

Assessing the validity of the 2hR method against traditional 24-hour recalls (24hRs) and objective biomarkers.

METHODS

Dietary intake was assessed in 215 Dutch adults on six randomly selected non-consecutive days (i.e., three 2hR-days and three 24hRs) during a four-week period. Sixty-three participants provided four 24-hour urine samples, to assess urinary nitrogen and potassium concentrations.

RESULTS

Intake estimates of energy (2,052±503 kcal vs. 1,976±483 kcal) and nutrients (e.g., protein: 78±23 g vs. 71±19 g; fat: 84±30 g vs. 79±26 g; carbohydrates: 220±60 g vs. 216±60 g) were slightly higher with 2hR-days than 24hRs. Comparing self-reported protein and potassium intakes to urinary nitrogen and potassium concentrations indicated a slightly higher accuracy of 2hR-days than 24hRs (protein: -14% vs. -18%; potassium: -11% vs. -16%). Correlation coefficients between methods ranged from 0.41 to 0.75 for energy and macronutrients and from 0.41 to 0.62 for micronutrients. Generally regularly consumed food groups showed small differences in intake (<10%) and good correlations (>0.60). Intakes of and energy, nutrients and food groups showed similar reproducibility (ICC) for 2hR-days and 24hRs.

CONCLUSIONS

Comparing 2hR-days with 24hRs showed relatively similar group-level bias for energy, most nutrients, and food groups. Differences were mostly due to higher intake estimates by 2hR-days. Biomarker comparisons showed less underestimation by 2hR-days as compared to 24hRs, suggesting that 2hR-days are a valid approach to assess intake of energy, nutrients and food groups.

TRIAL REGISTRATION

This trial was registered at the Dutch Central Committee on Research Involving Human Subjects (CCMO) registry as ABR. No. NL69065.081.19.

Validation of a Phosphorus Food Frequency Questionnaire in Patients with Kidney Failure Undertaking Dialysis

Nutritional guidelines recommended limiting dietary phosphorus as part of phosphorus management in patients with kidney failure. Currently, there is no validated phosphorus food frequency questionnaire (P-FFQ) to easily capture this nutrient intake. An FFQ of this type would facilitate efficient screening of dietary sources of phosphorus and assist in developing a patient-centered treatment plan. The objectives of this study were to develop and validate a P-FFQ by comparing it with the 24 hr multi-pass recall. Fifty participants (66% male, age 70 ± 13.3 years) with kidney failure undertaking dialysis were recruited from hospital nephrology outpatient departments. All participants completed the P-FFQ and 24 hr multi-pass recalls with assistance from a renal dietitian and then analysed using nutrient analysis software. Bland-Altman analyses were used to determine the agreement between P-FFQ and mean phosphorus intake from three 24 hr multi-pass recalls. Mean phosphorous intake was 1262 ± 400 mg as determined by the 24 hr multi pass recalls and 1220 ± 348 mg as determined by the P-FFQ. There was a moderate correlation between the P-FFQ and 24 hr multi pass recall (r = 0.62, p = 0.37) with a mean difference of 42 mg (95% limits of agreement: 685 mg; -601 mg, p = 0.373) between the two methods. The precision of the P-FFQ was 3.33%, indicating suitability as an alternative to the 24 hr multi pass recall technique. These findings indicate that the P-FFQ is a valid, accurate, and precise tool for assessing sources of dietary phosphorus in people with kidney failure undertaking dialysis and could be used as a tool to help identify potentially problematic areas of dietary intake in those who may have a high serum phosphate.

Toward Systems Models for Obesity Prevention: A Big Role for Big Data

The relation among the various causal factors of obesity is not well understood, and there remains a lack of viable data to advance integrated, systems models of its etiology. The collection of big data has begun to allow the exploration of causal associations between behavior, built environment, and obesity-relevant health outcomes. Here, the traditional epidemiologic and emerging big data approaches used in obesity research are compared, describing the research questions, needs, and outcomes of 3 broad research domains: eating behavior, social food environments, and the built environment. Taking tangible steps at the intersection of these domains, the recent European Union project "BigO: Big data against childhood obesity" used a mobile health tool to link objective measurements of health, physical activity, and the built environment. BigO provided learning on the limitations of big data, such as privacy concerns, study sampling, and the balancing of epidemiologic domain expertise with the required technical expertise. Adopting big data approaches will facilitate the exploitation of data concerning obesity-relevant behaviors of a greater variety, which are also processed at speed, facilitated by mobile-based data collection and monitoring systems, citizen science, and artificial intelligence. These approaches will allow the field to expand from causal inference to more complex, systems-level predictive models, stimulating ambitious and effective policy interventions.

Development and evaluation of a diet quality screener to assess adherence to the Dutch food-based dietary guidelines

The Eetscore FFQ was developed to score the Dutch Healthy Diet index 2015 (DHD2015-index) representing the Dutch food-based dietary guidelines of 2015. This paper describes the development of the Eetscore FFQ, a short screener assessing diet quality, examines associations between diet quality and participants' characteristics, and evaluates the relative validity and reproducibility of the Eetscore FFQ in a cross-sectional study with Dutch adults. The study sample consisted of 751 participants, aged 19-91 years, recruited from the EetMeetWeet research panel. The mean DHD2015-index score based on the Eetscore FFQ of the total sample was 111 (sd 17·5) out of a maximum score of 160 points and was significantly higher in women than in men, positively associated with age and education level, and inversely associated with BMI. The Kendall's tau-b coefficient of the DHD2015-index between the Eetscore FFQ and the full-length FFQ (on average 1·7-month interval, n 565) was 0·51 (95 % CI 0·47, 0·55), indicating an acceptable ranking ability. The intraclass correlation coefficient between DHD2015-index scores derived from two repeated Eetscore FFQ (on average 3·8-month interval, n 343) was 0·91 (95 % CI 0·89, 0·93) suggesting a very good reproducibility. In conclusion, the Eetscore FFQ was considered acceptable in ranking participants according to their diet quality compared with the full-length FFQ and showed good to excellent reproducibility.

Development and external validation of the 'Flower-FFQ': a FFQ designed for the Lifelines Cohort Study

Objective:

FFQ assess habitual dietary intake and are relatively inexpensive to process, but may take up to 60 min to complete. This article describes the validation of the Flower-FFQ, which consists of four short FFQ measuring the intake of energy and macronutrients or specific (micro)nutrients/foods that can be merged into one complete daily assessment using predefined algorithms.

Design:

Participants completed the Flower-FFQ and validated regular-FFQ (n 401). Urinary N (n 242) and K excretions (n 361) were measured. We evaluated: (1) group-level bias, (2) correlations and (3) cross-classification.

Setting:

Observational study.

Participants:

Dutch adults, 54 ± 11 (mean ± SD) years.

Results:

Flower-FFQ1, Flower-FFQ2, Flower-FFQ3 and Flower-FFQ4 were completed in ±24, 9, 8 and 9 min (±50 min total), respectively. The regular-FFQ was completed in ±43 min. Mean energy (flower v. regular: 7953 v. 8718 kJ/d) and macronutrient intakes (carbohydrates: 204 v. 222 g/d; protein: 75 v. 76 g/d; fat: 74 v. 83 g/d; ethanol: 8 v. 12 g/d) were comparatively similar. Spearman correlations between Flower-FFQ and regular-FFQ ranged from 0·60 to 0·80 for macronutrients and from 0·40 to 0·80 for micronutrients and foods. For all micronutrients and foods, ≥ 78 % of the participants classified in the same/adjacent quartile. The Flower-FFQ underestimated urinary N and K excretions by 24 and 18 %; 75 and 73 % of the participants ranked in the same/adjacent quartile.

Conclusion:

Completing the Flower-FFQ required 50 min with a maximum of 25 min per short FFQ. The Flower-FFQ has a moderate to good ranking ability for most nutrients and foods and performs sufficiently to study diet–disease associations.