Perspectives of Dietary Assessment in Human Health and Disease

Diet and human health have a complex set of relationships, so it is crucial to identify the cause-effects paths and their management. Diet is crucial for maintaining health (prevention) and unhealthy diets or diet components can cause disease in the long term (non-communicable disease) but also in the short term (foodborne diseases). The present paper aims to provide a synthesis of current research in the field of dietary assessment in health and disease as an introduction to the special issue on “Dietary Assessment and Human Health and Disease”. Dietary assessment, continuously evolving in terms of methodology and tools, provides the core information basis for all the studies where it is necessary to disentangle the relationship between diet and human health and disease. Estimating dietary patterns allows for assessing dietary quality, adequacy, exposure, and environmental impact in nutritional surveillance so on the one hand, providing information for further clinical studies and on another hand, helping the policy to design tailored interventions considering individual and planetary health, considering that planetary health is crucial for individual health too, as the SARS-CoV-2 (COVID-19) pandemic has taught. Overall, dietary assessment should be a core component in One-Health-based initiatives to tackle public health nutrition issues.     

History of Nutrition: The Long Road Leading to the Dietary Reference Intakes for the United States and Canada

The Dietary Reference Intakes (DRIs) are reference values to guide the planning and assessing of nutrient intakes in the United States and Canada. The DRI framework was conceptualized in 1994, and the first reports were issued from 1997–2004, based on work by expert panels and subcommittees under the guidance of the Food and Nutrition Board of the Institute of Medicine. Numerous conventions, challenges, and controversies were encountered during the process of defining and setting the DRIs, including the definition of the framework, the use of chronic disease endpoints, lack of data on requirements for children and youth, and methods for addressing nonessential bioactive substances with potential health benefits. DRIs may be used to plan and assess the nutrient intakes of both individuals and population groups, but the new paradigm particularly improved methods used for groups. It is now possible to estimate both the prevalence of inadequate intake and the prevalence of potentially excessive intake within a group. The DRIs have served as a potent influence on national nutrition policies, including those related to dietary guidance, food labeling, nutrition monitoring, food assistance programs, and military nutrition standards. Because of this important impact on nutrition policy, the DRIs must be based on the best possible and most up-to-date science. Unfortunately, no updates to specific DRIs are currently planned. Despite the long and challenging road that led to the current DRIs, it must not finish in a dead end. Monetary resources and political will are crucial to maintaining and continuously updating the DRIs.     

Using Short-Term Dietary Intake Data to Address Research Questions Related to Usual Dietary Intake among Populations and Subpopulations: Assumptions,Statistical Techniques,and Considerations

Many research questions focused on characterizing usual, or long-term average, dietary intake of populations and subpopulations rely on short-term intake data. The objective of this paper is to review key assumptions, statistical techniques, and considerations underpinning the use of short-term dietary intake data to make inference about usual dietary intake. The focus is on measurement error and strategies to mitigate its effects on estimated characteristics of population-level usual intake, with attention to relevant analytic issues such as accounting for survey design. Key assumptions are that short-term assessments are subject to random error only (i.e., unbiased for individual usual intake) and that some aspects of the error structure apply to all respondents, allowing estimation of this error structure in data sets with only a few repeat measures per person. Under these assumptions, a single 24-hour dietary recall per person can be used to estimate group mean intake; and with as little as one repeat on a subsample and with more complex statistical techniques, other characteristics of distributions of usual intake, such as percentiles, can be estimated. Related considerations include the number of days of data available, skewness of intake distributions, whether the dietary components of interest are consumed nearly daily by nearly everyone or episodically, the number of correlated dietary components of interest, time-varying nuisance effects related to day of week and season, and variance estimation and inference. Appropriate application of assumptions and recommended statistical techniques allows researchers to address a range of research questions, though it is imperative to acknowledge systematic error (bias) in short-term data and its implications for conclusions.     

Evaluation of Dietary Intake and Anthropometric Status in 1–9-Year-Old Children Living in Serbia: National Food Consumption Survey according to the EU Menu Methodology

The Serbian Food Consumption Survey among 1–9-year-old-children was conceptualized and conducted in compliance with the principles, established protocols, and guidelines of the EU Menu project between 2017 and 2021. Valid data were collected for 576 individuals (290 1–3-year-old toddlers and 276 3–9-year-old children). Regardless of age and gender category, the majority (68.80%) of children had normal weights according to the Body Mass Index-for-age classification system. The median daily energy intake was 1406.71 kcal with no differences between the settlement types. The overall median contributions of carbohydrates, protein, and fat to the total energy intake were 47.54%, 14.06%, and 37.88%, respectively. The proportions of the macronutrient intake deviated from the dietary reference values with compliance to the recommendations being particularly poor for fat and fiber. The consumption of energy-dense food groups such as meat and meat products, fat and oil, sugar, and confections was more pronounced among older children. The survey results provide a valuable insight into the nutritional status and dietary habits of toddlers and children 1–9 years old living in Serbia. They may serve as an evidence platform for public health programs, a valuable asset for decision-makers, and a reliable reference to guide nutritional policies, diet monitoring, and interventions targeting this population group in the future.     

Gender and age group differences in nutrition intake and dietary quality of Korean adults eating alone: based on Korean National Health and Nutrition Examination Survey Data, 2013–2016

BACKGROUND/OBJECTIVESThis study investigated gender and age differences in nutrient intake and dietary quality of people eating alone.SUBJECTS/METHODSFrom Korean National Health and Nutrition Examination Survey 2013–2016 data, 2,305 adults aged 20 years and older that ate meals alone were included in this study. Their energy and nutrients intakes, as well as their nutrient adequacy ratio (NAR), mean adequacy ratio (MAR), and index of nutritional quality (INQ) were analyzed. Food group consumption pattern, dietary variety score (DVS), dietary diversity score (DDS) were also analyzed. All data were compared among gender and age groups.RESULTSMen consumed more energy and nutrients than women, except for vitamin C, and the NARs showed similar gender differences. The INQs of 4 nutrients (calcium, vitamin A, vitamin C, and riboflavin) were lower than 1.0 in men, whereas only the calcium INQ was lower than 1.0 in women. Men had a lower DDS (3.6) than women (3.9) (P < 0.001) and had more ‘undesirable’ food group consumption patterns than women (P < 0.001). The intakes of calcium, vitamin A, and vitamin C were relatively low in the young-aged group (INQs less than 1.0). In the old-aged group, the MAR level was relatively low, and the INQs of calcium, riboflavin, and niacin were below 1.0. The old-aged group consumed more menu items, but their DVS was the lowest.CONCLUSIONSCompared to women, the dietary quality and food diversity among men were poorer. There were poorer quality and diversity patterns in the young-aged group compared to those of the older groups. An overall low intake of nutrients and the low nutrient density of meals were the main dietary problems among the old-aged group who eat alone. Therefore, men, particularly young- and old-aged, need to be prioritized in nutritional policies directed toward those who eat alone.     

DIetary ASSessment (DIASS) Study: Design of an Evaluation Study to Assess Validity,Usability and Perceived Burden of an Innovative Dietary Assessment Methodology

During recent years, the integration of technology has substantially improved self-reported dietary assessment methods, such as food frequency questionnaires (FFQ), food records, and 24-h recalls. To further reduce measurement error, additional innovations are urgently needed. Memory-related measurement error is one of the aspects that warrants attention, which is where new smartphone technologies and ecological momentary assessment (EMA) approaches provide a unique opportunity. In this article, we describe the DIASS study, which was designed to evaluate an innovative 2-h recall (2hR) smartphone-based methodology, against traditional 24-h recalls, FFQ, and biomarkers, to assess both actual and habitual dietary intake. It is hypothesized that a 2-h reporting window decreases reliance on memory and reporting burden, and increases data accuracy. We included 215 men (28%) and women (72%), with a mean ± SD age of 39 ± 19 years and a mean ± SD BMI of 23.8 ± 4.0. Most participants were highly educated (58%). Response rates for the various dietary assessment methods were >90%. Besides the evaluation of the accuracy, usability, and perceived burden of the 2hR methodology, the study set-up also allows for (further) evaluation of the other administrated dietary assessment tools.     

Physical Activity,Sedentary Behavior,and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research

BackgroundAdvances in automated data processing and machine learning (ML) models, together with the unprecedented growth in the number of social media users who publicly share and discuss health-related information, have made public health surveillance (PHS) one of the long-lasting social media applications. However, the existing PHS systems feeding on social media data have not been widely deployed in national surveillance systems, which appears to stem from the lack of practitioners and the public’s trust in social media data. More robust and reliable data sets over which supervised ML models can be trained and tested reliably is a significant step toward overcoming this hurdle. The health implications of daily behaviors (physical activity, sedentary behavior, and sleep [PASS]), as an evergreen topic in PHS, are widely studied through traditional data sources such as surveillance surveys and administrative databases, which are often several months out-of-date by the time they are used, costly to collect, and thus limited in quantity and coverage.ObjectiveThe main objective of this study is to present a large-scale, multicountry, longitudinal, and fully labeled data set to enable and support digital PASS surveillance research in PHS. To support high-quality surveillance research using our data set, we have conducted further analysis on the data set to supplement it with additional PHS-related metadata.MethodsWe collected the data of this study from Twitter using the Twitter livestream application programming interface between November 28, 2018, and June 19, 2020. To obtain PASS-related tweets for manual annotation, we iteratively used regular expressions, unsupervised natural language processing, domain-specific ontologies, and linguistic analysis. We used Amazon Mechanical Turk to label the collected data to self-reported PASS categories and implemented a quality control pipeline to monitor and manage the validity of crowd-generated labels. Moreover, we used ML, latent semantic analysis, linguistic analysis, and label inference analysis to validate the different components of the data set.ResultsLPHEADA (Labelled Digital Public Health Dataset) contains 366,405 crowd-generated labels (3 labels per tweet) for 122,135 PASS-related tweets that originated in Australia, Canada, the United Kingdom, or the United States, labeled by 708 unique annotators on Amazon Mechanical Turk. In addition to crowd-generated labels, LPHEADA provides details about the three critical components of any PHS system: place, time, and demographics (ie, gender and age range) associated with each tweet.ConclusionsPublicly available data sets for digital PASS surveillance are usually isolated and only provide labels for small subsets of the data. We believe that the novelty and comprehensiveness of the data set provided in this study will help develop, evaluate, and deploy digital PASS surveillance systems. LPHEADA will be an invaluable resource for both public health researchers and practitioners.     

“Just So You Know,It Has Been Hard”: Food Retailers’ Perspectives of Implementing a Food and Nutrition Policy in Public Healthcare Settings

Mandated policies to improve food environments in public settings are an important strategy for governments. Most Australian governments have mandated policies or voluntary standards for healthy food procurement in healthcare facilities, however, implementation and compliance are poor. A better understanding of the support required to successfully implement such policies is needed. This research explored food retailers’ experiences in implementing a mandated food and nutrition policy (the Policy) in healthcare settings to identify barriers, enablers, and impacts of compliance. Three 90-min workshops facilitated by two public health practitioners were undertaken with 12 food retailers responsible for operating 44 outlets across four hospitals in Perth, Western Australia. Workshop discussions were transcribed non-verbatim and inductive thematic content was analyzed. Three main themes were identified: (1) food retailers had come to accept their role in implementing the Policy; (2) the Policy made it difficult for food retailers to operate successfully, and; (3) food retailers needed help and support to implement the Policy. Findings indicate the cost of implementation is borne by food retailers. Communications campaigns, centralized databases of classified products, reporting frameworks, recognition of achievements, and dedicated technical expertise would support achieving policy compliance. Feasibility assessments prior to policy implementation are recommended for policy success.     

The Influence of Sociodemographic Factors,Lifestyle, and Risk Perception on Dietary Patterns in Pregnant Women Living in Highly Contaminated Areas: Data from the NEHO Birth Cohort

During pregnancy, maternal nutrition and lifestyle play a critical role in influencing fetal development and newborn health outcomes. The aim of this study is to investigate the factors influencing the adherence to dietary patterns in pregnant women living in highly contaminated areas, and whether women with higher environmental risk perception manifest different nutritional behaviors during pregnancy. Food consumption data on 816 pregnant women from the Neonatal Environment and Health Outcomes (NEHO) residential birth cohort were analyzed. Dietary patterns were computed by principal component analysis. A multinomial logistic regression was also applied to identify sociodemographic, lifestyle, and pregnancy-related determinants of adherence to dietary patterns during pregnancy. Three patterns of food consumption—explaining 24.9% of the total variance—were identified as “prudent”, “high energy”, and “vegetarian” patterns. Results suggest that food choices during pregnancy follow a social gradient and align with other health behaviors during pregnancy: older, better educated, and physically active women with higher risk perception are more likely to follow healthier dietary patterns. Knowledge about what is eaten can contribute to dietary choices. Interventions to improve the prenatal nutrition knowledge of pregnant women are needed, especially concerning younger mothers and those with lower educational levels.