Nutritional Epidemiological Studies Research Articles

ShaFA, a New Microsoft Windows-Based Software for Food Intake Analysis

In food intake studies, converting eaten foods into calories and nutrients and other food components using books and tables of food ingredients is a very time-consuming and error-prone task. ShaFA is new Microsoft Windows-based software for food component derivation of individual and group food intake data. This software is developed using C sharp programming language. Microsoft Access has been used to put the information of 8790 food types and their 85 food components based on the USDA-SR28 in the database of software. The user is capable to search in the database for desired food by the name or special code of the food and select them for each person. Each person’s food intake data can be stored via allocating an exclusive ID. Finally, the user can get a report of the imported data in a new window, and also can get a Microsoft Excel export which can be imported into statistical software such as SPSS and STATA. Each research project data can be stored in a file with the unique extension (ShaFA) which can be opened and edited in any system that its operating system is Microsoft Windows, and has ShaFA software installed on it. This software can provide researchers with valuable information in a short time, especially nutritional epidemiology studies. It can also be used in food industry to extract the information needed to label and complete food information table for a variety of food industry products.

Algorithm-based mapping of products in a branded Canadian food and beverage database to their equivalents in Health Canada's Canadian Nutrient File.

There is increasing recognition of the value of linking food sales databases to national food composition tables for population nutrition research. Expanding upon automated and manual database mapping approaches in the literature, our aim was to match 1,179 food products in the Canadian data subset of Euromonitor International's Passport Nutrition to their closest respective equivalents in Health Canada's Canadian Nutrient File (CNF). Matching took place in two major steps. First, an algorithm based on thresholds of maximal nutrient difference (between Euromonitor and CNF foods) and fuzzy matching was executed to offer match options. If a nutritionally appropriate match was available among the algorithm suggestions, it was selected. When the suggested set contained no nutritionally sound matches, the Euromonitor product was instead manually matched to a CNF food or deemed unmatchable, with the unique addition of expert validation to maximize meticulousness in matching. Both steps were independently performed by at least two team members with dietetics expertise. Of 1,111 Euromonitor products run through the algorithm, an accurate CNF match was offered for 65% of them; missing or zero-calorie data precluded 68 products from being run in the algorithm. Products with 2 or more algorithm-suggested CNF matches had higher match accuracy than those with one (71 vs. 50%, respectively). Overall, inter-rater agreement (reliability) rates were robust for matches chosen among algorithm options (51%) and even higher regarding whether manual selection would be required (71%); among manually selected CNF matches, reliability was 33%. Ultimately, 1,152 (98%) Euromonitor products were matched to a CNF equivalent. Our reported matching process successfully bridged a food sales database's products to their respective CNF matches for use in future nutritional epidemiological studies of branded foods sold in Canada. Our team's novel utilization of dietetics expertise aided in match validation at both steps, ensuring rigor and quality of resulting match selections.

Comparison of dimension reduction methods for the identification of heart-healthy dietary patterns

Most nutritional epidemiology studies investigating diet-disease trends use unsupervised dimension reduction methods, like principal component regression (PCR) and sparse PCR (SPCR), to create dietary patterns. Supervised methods, such as partial least squares (PLS), sparse PLS (SPLS), and Lasso, offer the possibility of more concisely summarizing the foods most related to a disease. In this study we evaluate these five methods for interpretable reduction of food frequency questionnaire (FFQ) data when analyzing a univariate continuous cardiac-related outcome via a simulation study and data application. We also demonstrate that to control for covariates, various scientific premises require different adjustment approaches when using PLS. To emulate food groups, we generated blocks of normally distributed predictors with varying intra-block covariances; only nine of 24 predictors contributed to the normal response. When block covariances were informed by FFQ data, the only methods that performed variable selection were Lasso and SPLS, which selected two and four irrelevant variables, respectively. SPLS had the lowest prediction error, and both PLS-based methods constructed four patterns, while PCR and SPCR created 24 patterns. These methods were applied to 120 FFQ variables and baseline body mass index (BMI) from the Multi-Ethnic Study of Atherosclerosis, which includes 6814 participants aged 45-84, and we adjusted for age, gender, race/ethnicity, exercise, and total energy intake. From 120 variables, PCR created 17 BMI-related patterns and PLS selected one pattern; SPLS only used five variables to create two patterns. All methods exhibited similar predictive performance. Specifically, SPLS’s first pattern highlighted hamburger and diet soda intake (positive associations with BMI), reflecting a fast food diet. By selecting fewer patterns and foods, SPLS can create interpretable dietary patterns while maintaining predictive ability.

Implementation of Nutrigenetics and Nutrigenomics Research and Training Activities for Developing Precision Nutrition Strategies in Malaysia.

Nutritional epidemiological studies show a triple burden of malnutrition with disparate prevalence across the coexisting ethnicities in Malaysia. To tackle malnutrition and related conditions in Malaysia, research in the new and evolving field of nutrigenetics and nutrigenomics is essential. As part of the Gene-Nutrient Interactions (GeNuIne) Collaboration, the Nutrigenetics and Nutrigenomics Research and Training Unit (N2RTU) aims to solve the malnutrition paradox. This review discusses and presents a conceptual framework that shows the pathway to implementing and strengthening precision nutrition strategies in Malaysia. The framework is divided into: (1) Research and (2) Training and Resource Development. The first arm collects data from genetics, genomics, transcriptomics, metabolomics, gut microbiome, and phenotypic and lifestyle factors to conduct nutrigenetic, nutrigenomic, and nutri-epigenetic studies. The second arm is focused on training and resource development to improve the capacity of the stakeholders (academia, healthcare professionals, policymakers, and the food industry) to utilise the findings generated by research in their respective fields. Finally, the N2RTU framework foresees its applications in artificial intelligence and the implementation of precision nutrition through the action of stakeholders.

Risk reduction and prevention of cardiovascular diseases: biological mechanisms of lycopene

Background and aims: The conservational effects of dietary interventions as advantageous instruments in the primary and secondary prevention of cardiovascular disease (CVD) have gotten more attention in recent years. Numerous nutritional epidemiological studies have highlighted the ability of diets to decrease costly care and treatments as well as adverse side effects from standard treatments. Lycopene is a non-pro-vitamin A carotenoid that is present in tomatoes, processed tomato products, and different fruits like watermelon, autumn olive, gac, pink grapefruit, pink guava, papaya, sea buckthorn, and wolfberry. As one of the most powerful antioxidants among dietary tetraterpenoids, lycopene can also assist in lowering the risk of early death and extending life in patients with heart disease. By reducing the destructive effects of free radicals along with total and “bad” LDL cholesterol levels while increasing “good” HDL cholesterol, lycopene holds the power to reduce the risk factors of heart disease. Several studies have investigated a reduction of oxidized-LDL (oxLDL) cholesterol levels following lycopene consumption which supports these claims and suggests the conceivable function of lycopene in the blockage of oxidative stress-associated CVD. A negative correlation between serum lycopene concentration and mortality of people with metabolic syndrome was found. Over 10 years, researchers observed a 39% decreased chance of premature death in individuals with the metabolic disease who had the highest blood concentrations of lycopene. Lycopene’s protective impacts are especially beneficial in those with low blood antioxidant levels or high levels of oxidative stress. This includes older adults, smokers, and diabetic individuals or other vascular disorders. Lycopene intake has been thought to reduce the risk of obesity, insulin resistance, and diabetes mellitus.Lycopene acts as an antihypertensive agent by impeding the angiotensin-converting enzyme and improving the production of nitric oxide (NO) in the endothelium. The purpose of this review is to summarize the possible mechanisms of lycopene in the prevention of CVD. Keywords: Lycopene, Risk factors of heart disease, Antioxidants, Carotenoids, Cardio-metabolic, Insulin resistance

Diet, nutrition, and cognitive function: A narrative review of Japanese longitudinal studies.

In aging societies, the number of older people with cognitive decline and dementia is increasing. Proper nutrition is a key factor that can help in the prevention of these age-related impairments. This narrative review of longitudinal studies in Japan outlines the relationship between nutrition and the brain and focuses on Japanese nutritional epidemiologic studies. The results of Japanese cohort studies suggest that rather than a single food or nutrient, a nutritionally balanced diet that integrates a variety of foods and nutrients can contribute to the maintenance of brain function and be effective in preventing dementia. In addition, this review considers a nutritional approach to reducing the severity of cognitive decline in individuals with mild cognitive impairment and dementia, and suggests lifelong strategies for the prevention of cognitive decline. It is important that we consider the practice of eating not only as a way to obtain nutrients, but also as an important lifestyle habit to maintain our physical and mental health. Geriatr Gerontol Int 2022; 22: 825-831.

Protocol for a systematic review and meta-analysis: to investigate the association of adherence to plant-based diets with cardiovascular disease risk

Background:Plant-based diets (PBDs) are characterised as healthy dietary patterns that emphasise the intake of plant foods and limit the intake of animal foods. The Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets are common examples of healthy dietary patterns that are mainly plant based. There are different dietary pattern analysis approaches and scoring systems available to construct indices that measure adherence to a dietary pattern. Nutritional epidemiology studies necessitate the use of appropriate dietary indices when investigating diet-disease associations. This protocol is for a review that will: 1) evaluate how a PBD has been defined in studies published globally; and 2) assess the methods used to construct dietary indices that measure adherence to a PBD; with a focus on studies that have assessed the association between adherence to a PBD and CVD risk. Methods:This protocol was developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis Protocols guidelines. PubMed–Medline, Scopus and biomedical databases within EBSCOhost will be searched up to August 2021. Two reviewers will independently screen the identified records and review the eligible full texts for inclusion. Discrepancies will be resolved by consensus or through discussion with a third reviewer. Meta-analysis will be performed where possible and consistency of the findings checked through subgroup analysis. Heterogeneity across studies will be assessed and quantified, and publication bias investigated. Relevant sensitivity analyses will be performed to substantiate the robustness of the study findings. Conclusion:Currently, there is some inconsistency in defining and measuring adherence to a PBD across study populations. Moreover, a lack of global data on the association between adherence to a PBD and CVD risk. This systematic review could aid in promoting the worldwide uptake of these findings for policy and practice purposes. This research will use previously published studies; and therefore, will not require ethical approval.

Predictive Utility of Composite Child Feeding Indices (CCFIs) for Child Nutritional Status: Comparative Analyses for the Most Suitable Formula for Constructing an Optimum CCFI.

Composite child feeding indices (CCFIs) developed from various relevant measures of dietary intake by infants and young children have several potential applications in nutritional epidemiological studies for the development and deployment of precise public health nutrition interventions against child undernutrition. The predictive utility of some CCFIs (computed from varying formulation components) for child nutritional status (stunting, wasting, and underweight) were compared. The purpose of the study was to identify the most suitable among them for possible standardization, validation, and adoption by nutritional health researchers. Using cluster sampling, data from 581 mother–child pairs were collected. Multivariable regression analyses were applied to the data obtained through a community-based analytical cross-sectional survey design. Three of the CCFIs were found to be significantly associated with only wasting (WHZ) from the linear regression models after adjusting for potential confounders and/or correlates. None of the CCFIs (whether in the continuous nor categorical form) was consistently predictive of all three measures of child nutritional status, after controlling for potential confounders and/or correlates, irrespective of the choice of regression method. CCFI 5 was constructed using a dimension reduction technique—namely principal component analysis (PCA)—as the most optimal summary index in terms of predictiveness for child wasting status, validity, and reliability (Cronbach’s α = 0.80) that captured relevant dimensions of optimal child food intake. The dimension reduction approach that was used in constructing CCFI 5 is recommended for standardization, validation, and possible adoption for wider applicability across heterogeneous population settings as an optimum CCFI usable for nutritional epidemiological studies among children under five years.

Total Energy Intake: Implications for Epidemiologic Analyses.

In 1986, Willett and Stampfer propelled the nutritional epidemiology field forward by publishing a commentary emphasizing the importance of analyzing diet in relation to total energy intake in epidemiologic analyses of diet and disease, detailing the value of accounting for body size, physical activity, and metabolic efficiency in diet-disease analyses via energy intake adjustment. Their publication has since been cited over 2,886 times and has inarguably advanced methodology for studying diet-disease associations, with most nutritional epidemiology studies standardly including some form of energy adjustment. However, there remains debate regarding the best scenarios and methods for energy adjustment. The goals of this commentary are to provide an updated review on factors that account for inter-individual differences in energy intake, provide a balanced discussion regarding the considerations for or against adjustment for energy intake, and provide an updated examination of the commonly employed methods for the analysis of nutrient-disease associations. The principles of energy adjustment continue to be relevant nearly 25 years later, as it remains a critical method to account for potentially confounding inter-individual variations in body size and physical activity.

Association of healthy beverage index with circadian rhythm and quality of sleep among overweight and obese women: a cross-sectional study.

Circadian rhythm is a behavioral, physiological, and molecular change with a cycle length of approximately 24h. Changes to the circadian rhythm can result in sleep difficulty. The healthy beverage index (HBI) is a holistic concept for evaluating the quality of overall beverage intake and its association with health-related outcomes in nutritional epidemiological studies. This study aimed to assess the relationship of HBI with circadian rhythm and sleep quality among overweight/obese women. The current study was conducted among 208 overweight and obese women between 18-48years in Tehran, Iran. We evaluated potential HBI with a valid food frequency questionnaire. Following standard procedures, trained personnel assessed anthropometric measures, blood samples, and other baseline characteristics. The Pittsburgh Sleep Quality Index and the morning-eveningness questionnaire were applied to evaluate sleep quality and circadian rhythm respectively. The mean (SD) BMI for this study was 30.8 (4.2) kg/m2. We observed that subjects in the least tertile had significantly high levels of triglyceride (p = 0.04) and low-density lipoprotein (p = 0.009). High-density lipoprotein was significantly different across the tertiles (p = 0.003). After adjusting for potential covariates, subjects in the second tertile of HBI had 5.07 odds of having the worst quality of sleep as compared to those in the third tertile, p < 0.05. We also observed a significant inverse association between the HBI and the "moderately evening type" participants (OR 0.86; 95% CI 0.68-0.99; p: 0.02) after adjusting for potential confounders. Healthy beverage consumption may have the potential of improving sleep quality among overweight and obese subjects. Level IV, evidence obtained from a descriptive study.

A high-throughput platform for the rapid screening of vitamin D status by direct infusion-MS/MS

Vitamin D is an important fat-soluble prohormone with pleiotropic effects on human health, such as immunomodulation of the innate and adaptive immune system. There is an unmet clinical need for a rapid screening platform for 25-hydroxyvitamin D (25OH-D) determination without chromatographic separation that offers better precision and accuracy than immunoassays. Here, we introduce a high-throughput method for assessing vitamin D status from blood specimens based on direct infusion-MS/MS (DI-MS/MS) following click derivatization using 2-nitrosopyridine. We developed an optimized liquid-phase extraction protocol to minimize ion suppression when directly infusing serum or plasma extracts via a capillary electrophoresis system for quantitative determination of 25OH-D. Acceptable reproducibility (mean coefficient of variation = 10.9%, n = 412), recovery (mean = 102% at 15, 30, and 45 nmol/l), and linearity (R2 > 0.998) were achieved for 25OH-D with lower detection limits (limit of detection ∼1.2 nmol/l, S/N ∼ 3), greater throughput (∼3 min/sample), and less bias than a commercial chemiluminescence immunoassay prone to batch effects. There was mutual agreement in 25OH-D concentrations from reference blood samples measured by DI-MS/MS as compared with LC-MS/MS (mean bias = 7.8%, n = 18). We also demonstrate that this method could reduce immunoassay misclassification of vitamin D deficiency in a cohort of critically ill children (n = 30). In conclusion, DI-MS/MS offers a viable alternative to LC-MS/MS for assessment of vitamin D status in support of large-scale studies in nutritional epidemiology as well as clinical trials to rapidly screen individual patients who may benefit from vitamin D supplementation.

Widening the Perspectives for Legume Consumption: The Case of Bioactive Non-nutrients.

Legume grains have provided essential nutrients in human diets for centuries, being excellent sources of proteins, carbohydrates, fatty acids, and fibers. They also contain several non-nutrients that historically have been connotated as toxic but that in recent years have been shown to have interesting bioactive properties. The discussion on the role of bioactive non-nutrients is becoming more important due to increasing science-based evidence on their potential antioxidant, hypoglycemic, hypolipidemic, and anticarcinogenic properties. At a time when legume-based products consumption is being strongly promoted by national governments and health authorities, there is a need to clearly define the recommended levels of such non-nutrients in human diets. However, there is insufficient data determining the ideal amount of non-nutrients in legume grains, which will exert the most positive health benefits. This is aligned with insufficient studies that clearly demonstrate if the positive health effects are due to the presence of specific non-nutrients or a result of a dietary balance. In fact, rather than looking directly at the individual food components, most nutritional epidemiology studies relate disease risk with the food and dietary patterns. The purpose of this perspective paper is to explore different types of non-nutrients present in legume grains, discuss the current evidence on their health benefits, and provide awareness for the need for more studies to define a recommended amount of each compound to identify the best approaches, either to enhance or reduce their levels.

Validity and Reliability of Semiquantitative Food Frequency Questionnaires for Assessing Nutrient Intake among Preschool Children in Northwest China.

Background Considering the lack of valid and reliable food frequency questionnaires (FFQs) for nutritional epidemiological studies in China, it is necessary to develop an effective one for assessing nutrient intake among preschool children. The aim of this study was to evaluate the validity and reliability of newly developed FFQs for assessing food and nutrient intakes among preschool children in Northwest China. Methods Semiquantitative 67-item FFQs were developed and validated. In total, 326 children (aged 2–6 years) were recruited from three different cities in Northwest China. All subjects were asked to complete the FFQs twice with a six-month interval period for test-retest reliability. Apart from the FFQs, a 3-day food record (3-DFR) was also carried out to evaluate the validity of the FFQs. Results There was no significant difference in the nutrient intakes of preschool children between the two FFQs (P > 0.05), and these two FFQs demonstrated a positive correlation (P < 0.05). Spearman's coefficient correlation values ranged from 0.222 (“Selenium”) to 0.832 (“Energy”). The intraclass correlation coefficient values ranged from 0.282 (“Selenium”) to 0.882 (“Energy”). With regards to the validity of FFQs, nutrient intakes from FFQs were greater than 3DR dietary recalls (P < 0.05). After adjusting for total energy and intraindividual variation, all nutrient intakes showed a positive correlation (P < 0.05), and these correlations became stronger. According to the quartiles of nutrient intakes, the exact agreement between the FFQs and 3DR dietary recalls ranged between 40% (“Selenium”) and 70% (“Energy”), and grossly misclassified was low (12.5%). Conclusions The findings of this study indicate that the designed FFQs exhibit good test-retest reliability and moderate relative validity. Hence, the FFQs can serve as an important tool for the large-scale assessment of food and nutrient intakes among preschool children (in the mentioned areas of China).

Assessments of risk of bias in systematic reviews of observational nutritional epidemiologic studies are often not appropriate or comprehensive: a methodological study

BackgroundAn essential component of systematic reviews is the assessment of risk of bias. To date, there has been no investigation of how reviews of non-randomised studies of nutritional exposures (called...

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.

Bayesian model selection in additive partial linear models via locally adaptive splines

We provide a flexible framework for selecting among a class of additive partial linear models that allows both linear and nonlinear additive components. In practice, it is challenging to determine which additive components should be excluded from the model while simultaneously determining whether nonzero additive components should be represented as linear or non-linear components in the final model. In this paper, we propose a Bayesian model selection method that is facilitated by a carefully specified class of models, including the choice of a prior distribution and the nonparametric model used for the nonlinear additive components. We employ a series of latent variables that determine the effect of each variable among the three possibilities (no effect, linear effect, and nonlinear effect) and that simultaneously determine the knots of each spline for a suitable penalization of smooth functions. The use of a pseudo-prior distribution along with a collapsing scheme enables us to deploy well-behaved Markov chain Monte Carlo samplers, both for model selection and for fitting the preferred model. Our method and algorithm are deployed on a suite of numerical studies and are applied to a nutritional epidemiology study. The numerical results show that the proposed methodology outperforms previously available methods in terms of effective sample sizes of the Markov chain samplers and the overall misclassification rates.

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.

Protocol for a systematic review and meta-analysis: to investigate the association of adherence to plant-based diets with cardiovascular disease risk

Background: Plant-based diets (PBDs) are characterised as healthy dietary patterns that emphasise the intake of plant foods and limit the intake of animal foods. The Mediterranean and Dietary Approaches to Stop Hypertension (DASH) diets are common examples of healthy dietary patterns that are mainly plant based. There are different dietary pattern analysis approaches and scoring systems available to construct indices that measure adherence to a dietary pattern. Nutritional epidemiology studies necessitate the use of appropriate dietary indices when investigating diet-disease associations. Methods: This systematic review protocol was developed according to the Preferred Reporting Items for Systematic reviews and Meta-Analysis protocols (PRISMA-P) guidelines. PubMed–Medline, Scopus and relevant biomedical databases within EBSCOhost will be searched up to August 2021 using relevant key words. Two reviewers will independently screen the identified records and review the eligible full texts for inclusion. Discrepancies will be resolved by consensus or through discussion with a third reviewer. Appropriate meta-analysis will be performed where possible and consistency of the findings checked through subgroup analysis. Heterogeneity across studies will be assessed and quantified, and publication bias investigated. Relevant sensitivity analyses will be performed to substantiate the robustness of the study findings. Conclusion: Currently, there is some inconsistency in defining and measuring adherence to a PBD across study populations. In addition to this, a lack of global data on the association between adherence to a PBD and CVD risk. This systematic review could aid in promoting the worldwide uptake of these findings for policy and practice purposes. This research will use previously published studies; and therefore, will not require ethical approval.

Development and Usability Study of an Open-Access Interviewer-Administered Automated 24-h Dietary Recall Tool in Argentina: MAR24

Background: Latin American countries show a fast-growing rate of non-communicable diseases (NCDs) and diet is a critical risk factor that must be properly assessed. Automated dietary assessment tools to collect 24-h dietary recalls (24HR) are lacking in Argentina.Objective: This study aimed to develop an open-access automated tool (MAR24) for collecting 24HR using a multiple pass method and a database containing foods and recipes commonly consumed in Argentina.Methods: MAR24 was developed based on data from 1,285 24HR provided by male and female participants aged 18 to 68 years from the six Argentinian geographical regions. The main structure and interface of the tool were designed using Visual Basic for Applications programming language in Excel Microsoft Office 365, integrating the five steps of the United States Department of Agriculture (USDA) Automated Multiple-Pass Method (AMPM) for the application of 24HR in Spanish. The tool underwent alpha testing and expert assessment to address structural and usability issues. Critical feedback and face validation from researchers and experienced dietitians, and repeated testing to collect 24HR were used to adjust and improve the tool.Results: A total of 968 food items and 100 standard Argentinian recipes were added to its database. MAR24 allows the estimation of the nutrient profile of dietary intake. The analytic food composition includes energy and 50 nutrients including water, macronutrients, total dietary fiber, total sugar, 10 minerals, 19 vitamins, eight fatty acids, cholesterol, ethyl alcohol, caffeine, and theobromine. MAR24 includes a user manual and technical manual to guide users to apply changes (e.g., add foods or recipes, or change food designation according to local terms) to fit different research and clinical applications.Conclusions: MAR24 is the first tool that uses the AMPM methodology for 24HR applications in Argentina. The tool may be used in clinical practice and clinical trials for monitoring purposes, and in validation of food frequency questionnaires (FFQ) for nutritional epidemiology studies addressing dietary-associated risk factors for NCDs.

An umbrella review of the evidence associating diet and cancer risk at 11 anatomical sites

There is evidence that diet and nutrition are modifiable risk factors for several cancers, but associations may be flawed due to inherent biases. Nutritional epidemiology studies have largely relied on a single assessment of diet using food frequency questionnaires. We conduct an umbrella review of meta-analyses of observational studies to evaluate the strength and validity of the evidence for the association between food/nutrient intake and risk of developing or dying from 11 primary cancers. It is estimated that only few single food/nutrient and cancer associations are supported by strong or highly suggestive meta-analytic evidence, and future similar research is unlikely to change this evidence. Alcohol consumption is positively associated with risk of postmenopausal breast, colorectal, esophageal, head & neck and liver cancer. Consumption of dairy products, milk, calcium and wholegrains are inversely associated with colorectal cancer risk. Coffee consumption is inversely associated with risk of liver cancer and skin basal cell carcinoma.