Evaluating Smartphone App Based Dietary Tracking in a Military Population: Validation Study (Preprint)

BACKGROUND Collecting dietary intake data is a key component for a majority of nutritional epidemiology studies. Smartphone technology advancements allow researchers to use health and nutrition apps as alternatives to currently available tools (food frequency questionnaires, 24-hour recalls, and food diaries). Service Members (SM) can greatly benefit from the always-available information and easily accessible nature of smartphones to track their intake. Clinicians working with military units can help provide these SM with the skills to evaluate their intake for performance benefits. Understanding the accuracy of these apps is important to determine their effectiveness for use in clinical and research settings. OBJECTIVE This study evaluated the relative validity of self-reported intake with the HealthWatch 360 (HW 360) app compared to the Automated Self-Administered 24-hour Dietary Assessment (ASA24). METHODS Recruitment targeted Army and Air Force SM from Joint Base Lewis-McChord, WA and Joint Base San Antonio-Lackland, TX who currently or previously failed to meet body composition standards. Participants (n=53) completed a demographic questionnaire, baseline anthropometric measurements, and recorded daily intake on the HW 360 app. They returned approximately two weeks later to complete a 24-hour recall using the ASA24. Agreement and relative validity were evaluated using Bland-Altman plots and two one-sided tests at a ± 10% equivalency range of ASA24 mean nutrient intake values between HW 360 and ASA24 data. Multilinear regressions analyzed relationships between participant demographics and relative validity. RESULTS HW 360 was not significantly equivalent to the ASA24. Large levels of underreporting were found in total energy (Mean Difference (Mdiff) = -503.3 kcal, 90% CI: -649.8 to -356.7 kcal), carbohydrates (Mdiff = -52.2 g, 90% CI: -70.4 to -34.1 g), protein (Mdiff = -20.4 g, 90% CI: -29.4 to -11.3 g), and fat (Mdiff = -24.6 g, 90% CI: -32.5 to -16.7 g). Bland-Altman plots failed to illustrate agreement. No significant correlations existed for demographic variables and relative validity. CONCLUSIONS Differences between all variables tested were above clinically significant values and limit the usage of this application in research and clinical settings. Further research is needed to determine the potential causes of underreporting and evaluate methods to minimize this effect. Understanding these effects allows the implementation of a tailored app for use with SM. It has the potential to be an invaluable asset for this population due the unpredictable nature of deployments and training exercises. CLINICALTRIAL ClinicalTrials.gov NCT04959318; https://clinicaltrials.gov/ct2/show/NCT04959318

Reproducibility and Validity of a Food Frequency Questionnaire (FFQ) Developed for Middle-Aged and Older Adults in Semarang, Indonesia

We assessed the reproducibility and validity of a food frequency questionnaire (FFQ) among middle-aged and older adults in Semarang, Indonesia. A total of 259 subjects aged 40–80 years completed two FFQs (nine-month apart) and nine 24 h dietary recalls (24HDRs, as a reference method). The reproducibility of the FFQ was analyzed using correlation coefficient, intra-class correlation coefficient (ICC), weighted kappa statistics and misclassification analysis. The validity was estimated by comparing the data acquired from FFQ1 and 24HDRs. The crude Pearson’s correlation coefficients and ICC for total energy and nutrients between FFQ1 and FFQ2 ranged from 0.50 to 0.81 and 0.44 to 0.78, respectively. Energy adjustment decreased the correlation coefficients for most nutrients. The crude, energy-adjusted and de-attenuated correlation coefficients for FFQ1 and 24HDRs ranged from 0.41 to 0.70, 0.31 to 0.89 and 0.54 to 0.82, respectively. The agreement rates for the same or adjacent quartile classifications were 81.1–94.6% for two FFQs and 80.7–89.6% for FFQ1 and 24HDRs. The weighted kappa values were 0.21 to 0.42 for two FFQs and 0.20 to 0.34 for FFQ1 and 24HDRs. A positive mean difference was found in the Bland–Altman analyses for energy and macronutrients. The FFQ could be acceptable for nutritional epidemiology study among Indonesians.

Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data

Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a “black box” approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.

Scientific production of Nutrition courses in Food and Nutrition in Collective Health: contributions to the debate on professional performance

This study aims to analyze the scientific production of Nutrition courses on knowledge core Food and Nutrition in Collective Health (FNCH) and its associations with institutional characteristics and advisor’s academic degree. A bibliometric study was performed on 195 final projects of five nutrition courses in Rio Grande do Norte state (Brazil) from the year 2013. Information related to higher education institutions and academic degree of advisor were collected. From the reading of sections of final projects, screening was performed on final project involvement with knowledge core FNCH, being collected general methodological characteristics, classification on sub cores of FNCH, and theme approached. Pearson’s chi-square test was used with a significance level at p-value ≤ 0.05 and 95% confidence interval in a univariate and bivariate way. From the total of analyzed final projects, 54 (27.7%) were related to knowledge core FNCH, prevailing final projects with a quantitative approach (61%), presented as scientific articles (57%), and performed in public services (45%). There was an emphasis on the sub-core of Nutritional Epidemiology (63%) [p < 0.001], with the theme Nutritional Assessment (57%) [p < 0.001]. There was no significant association between FNCH final projects proportion and institutional characteristics or advisor’s academic degree. Thinking about nutritionists’ practice, limitations were identified on FNCH scientific production, with an emphasis on nutritional diagnosis researches, with less involvement in public health policies and human and social sciences.

‘Energy-Dense, High-SFA and Low-Fiber’ Dietary Pattern Lowered Adiponectin but Not Leptin Concentration of Breast Cancer Survivors

Dietary pattern (DP) and its relationship with disease biomarkers have received recognition in nutritional epidemiology investigations. However, DP relationships with adipokines (i.e., adiponectin and leptin) among breast cancer survivors remain unclear. Therefore, we assessed relationships between DP and high-molecular weight (HMW) adiponectin and leptin concentration among breast cancer survivors. This cross-sectional study involved 128 breast cancer survivors who attended the oncology outpatient clinic at two main government hospitals in the East Coast of Peninsular Malaysia. The serum concentration of HMW adiponectin and leptin were measured using enzyme-linked immunosorbent assay (ELISA) kits. A reduced rank regression method was used to analyze DP. Relationships between DP with HMW adiponectin and leptin were examined using regression models. The findings show that with every 1-unit increase in the ‘energy-dense, high-SFA, low-fiber’ DP z-score, there was a reduction by 0.41 μg/mL in HMW adiponectin which was independent of age, BMI, education level, occupation status, cancer stage, and duration since diagnosis. A similar relationship with leptin concentration was not observed. In conclusion, the ‘energy-dense, high-saturated fat and low-fiber’ DP, which is characterized by high intake levels of sugar-sweetened drinks and fat-based spreads but low intake of fruits and vegetables, is an unhealthy dietary pattern and unfavorable for HMW adiponectin concentration, but not for leptin. These findings could serve as a basis in developing specific preventive strategies that are tailored to the growing population of breast cancer survivors.

Identification and Characterization of Human Observational Studies in Nutritional Epidemiology on Gut Microbiomics for Joint Data Analysis

In any research field, data access and data integration are major challenges that even large, well-established consortia face. Although data sharing initiatives are increasing, joint data analyses on nutrition and microbiomics in health and disease are still scarce. We aimed to identify observational studies with data on nutrition and gut microbiome composition from the Intestinal Microbiomics (INTIMIC) Knowledge Platform following the findable, accessible, interoperable, and reusable (FAIR) principles. An adapted template from the European Nutritional Phenotype Assessment and Data Sharing Initiative (ENPADASI) consortium was used to collect microbiome-specific information and other related factors. In total, 23 studies (17 longitudinal and 6 cross-sectional) were identified from Italy (7), Germany (6), Netherlands (3), Spain (2), Belgium (1), and France (1) or multiple countries (3). Of these, 21 studies collected information on both dietary intake (24 h dietary recall, food frequency questionnaire (FFQ), or Food Records) and gut microbiome. All studies collected stool samples. The most often used sequencing platform was Illumina MiSeq, and the preferred hypervariable regions of the 16S rRNA gene were V3–V4 or V4. The combination of datasets will allow for sufficiently powered investigations to increase the knowledge and understanding of the relationship between food and gut microbiome in health and disease.

Metabolomic profiling of the Dietary Approaches to Stop Hypertension (DASH) diet provides novel insights for the nutritional epidemiology of type 2 diabetes mellitus (T2DM)

Adherence to the DASH diet is inversely associated with T2DM risk. Metabolic changes due to DASH adherence and their potential relationship with incident T2DM have not been described. The objective is to determine metabolite clusters associated with adherence to a DASH-like diet in the Insulin Resistance Atherosclerosis Study (IRAS) cohort and explore if the clusters predicted 5-year incidence of T2DM. The current study included the 570 non-diabetic multi-ethnic participants aged 40 - 69 years. Adherence to a DASH-like diet was determined a priori through an 80-point scale for absolute intakes of the eight DASH food groups. Quantitative measurements of 87 metabolites (acylcarnitines, amino acids, bile acids, sterols, and fatty acids) were obtained at baseline. Metabolite clusters related to DASH adherence were determined through partial least squares (PLS) analysis using R. Multivariable-adjusted logistic regression (MLR) was used to explore the associations between metabolite clusters and incident T2DM. A group of acylcarnitines and fatty acids loaded strongly on the two components retained under PLS. Among strongly loading metabolites, a select group of acylcarnitines had over 50% of their individual variance explained by the PLS model. Component 2 was inversely associated with incident T2DM (Odds ratio (OR): 0.89; 95% Confidence interval (CI) 0.80-0.99, p-value = 0.043) after adjustment for demographic and metabolic covariates. Component 1 was not associated with T2DM risk (OR: 1.02; 95% CI 0.88-1.19, p-value = 0.74). Adherence to a DASH-type diet may contribute to reduced T2DM risk in part through modulations in acylcarnitine and fatty acid physiology.

194Nonlinear isocaloric substitution analysis in nutritional epidemiology: An example using the UK Biobank data

Background Intake of macronutrients and its components are associated with mortality and morbidity. Isocaloric substitution analysis is a tool to examine how changing the source of energy intake (e.g. from saturated to monounsaturated fat) is associated with health. However, conventional methods assume linearity, which may be untrue in many cases. This paper presents a nonlinear alternative, using UK Biobank data as an example data set. Methods Nonlinear isocaloric substitution analysis was conducted using penalised cubic splines in Cox proportional hazard models. In the UK Biobank, 195,658 participants completed at least one dietary questionnaire and were included in the analyses. Diet was assessed using the Oxford WebQ, a web-based 24-hour recall questionnaire. Prospective all-cause mortality was derived from on linked death records. Results More than half of the associations between macronutrient intake and all-cause mortality were nonlinear. Nonlinear isocaloric substitution analysis provides effect sizes conditional on the current intake, while conventional analysis provides an average over the whole range of intake. For example, conventional isocaloric substitution estimated no effect of replacing sugar with starch. However, the nonlinear method revealed that replacing sugar with starch was associated with a higher risk when the current starch intake was greater than 30% of total energy, and with a lower risk when current intake was less than 25%. Conclusions Nonlinear isocaloric substitution provides an alternative to conventional isocaloric substitution analysis when the underlying association is nonlinear. Key messages Nonlinear associations are common in nutritional epidemiology. In such cases, nonlinear isocaloric substitution analyses should be used.

Lowering the p-value threshold to alleviate information crisis in nutritional epidemiology – a possible temporary solution?

Nutritional epidemiology has often been criticized by its inconsistency of results, these that are broadcasted to the media due to the public interest in the topic. Effect sizes in nutritional epidemiology are often small and biases are present. The cut-off of statistically significant results in the field currently is by the norm of 5%, that is, p &lt; 0.05 equals to a positive finding. Recent evidence found that lowering this threshold makes less claims to hold true. This said, lowering the alpha level in nutritional epidemiology could reduce the scenario in the field characterized by high frequency of positive and probably implausible findings. Of course, this would require a culture shift towards encouragement of negative findings, already proposed in some fields of science.