Dietary and lifestyle inflammation scores in relation to colorectal cancer recurrence and all-cause mortality: A longitudinal analysis.

Aim: The aim of this study was to longitudinally investigate dietary and lifestyle inflammation scores and their interaction in relation to risk of colorectal cancer (CRC) recurrence and all-cause mortality.

Methods: Data of two prospective cohort studies among CRC survivors was used. Information about diet and/or lifestyle was available for 2739 individuals for at least one of the following time points: at diagnosis, six months after diagnosis and two years after diagnosis.

Estimating the contribution of overweight and obesity to ethnic inequalities in cardio-metabolic diseases in the Netherlands: a simulation study.

Objectives: Overweight and obesity (OWOB) starts in childhood, influences adult cardiovascular risk, and is not equally distributed across ethnic groups. It is unclear which effects can be expected from reductions in OWOB across the life course on inequalities in cardio-metabolic diseases in a multi-ethnic population. This study aims to estimate the effects of three scenarios of changes in OWOB (the Normal-Weight-for-All scenario, the No-Ethnic-Difference-over-the-Life-Course scenario, the and No-Ethnic-Differences-in-Childhood scenario).

A Model of Individual BMI Trajectories.

A risk factor model of body mass index (BMI) is an important building block of health simulations aimed at estimating government policy effects with regard to overweight and obesity. We created a model that generates representative population level distributions and that also mimics realistic BMI trajectories at an individual level so that policies aimed at individuals can be simulated. The model is constructed by combining several datasets.

Relative validity of habitual sugar and low/no-calorie sweetener consumption assessed by food frequency questionnaire, multiple 24-h dietary recalls and urinary biomarkers: an observational study within the SWEET project.

Background: Studies investigating associations between sweeteners and health yield inconsistent results, possibly due to subjective self-report dietary assessment methods.

Objectives: We compared the performance of a food frequency questionnaire (FFQ), multiple 24-h dietary recalls (24hRs), and urinary biomarkers to estimate intake of sugars and low/no-calorie sweeteners (LNCSs).

Methods: Participants (n = 848, age 54 ± 12 y) from a 2-y observational study completed 1 semiquantitative FFQ and ≥ 3 nonconsecutive 24hRs.

Constructing synthetic populations in the age of big data.

Background: To develop public health intervention models using micro-simulations, extensive personal information about inhabitants is needed, such as socio-demographic, economic and health figures. Confidentiality is an essential characteristic of such data, while the data should reflect realistic scenarios. Collection of such data is possible only in secured environments and not directly available for open-source micro-simulation models.

Adopting a child perspective for exposome research on mental health and cognitive development - Conceptualisation and opportunities.

Mental disorders among children and adolescents pose a significant global challenge. The exposome framework covering the totality of internal, social and physical exposures over a lifetime provides opportunities to better understand the causes of and processes related to mental health, and cognitive functioning. The paper presents a conceptual framework on exposome, mental health, and cognitive development in children and adolescents, with potential mediating pathways, providing a possibility for interventions along the life course.

Clinical reasoning in pharmacy: What do eye movements and verbal protocols tell us about the processing of a case task?

This study investigates pharmacy students' reasoning while solving a case task concerning an acute patient counselling situation in a pharmacy. Participants' (N = 34) reasoning processes were investigated with written tasks utilizing eye-tracking in combination with verbal protocols. The case was presented in three pages, each page being followed by written questions.

Predicting self-perceived general health status using machine learning: an external exposome study.

Background: Self-perceived general health (SPGH) is a general health indicator commonly used in epidemiological research and is associated with a wide range of exposures from different domains. However, most studies on SPGH only investigated a limited set of exposures and did not take the entire external exposome into account. We aimed to develop predictive models for SPGH based on exposome datasets using machine learning techniques and identify the most important predictors of poor SPGH status.

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

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

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

llperm: a permutation of regressor residuals test for microbiome data.

Background: Differential abundance testing is an important aspect of microbiome data analysis, where each taxa is fitted with a statistical test or a regression model. However, many models do not provide a good fit to real microbiome data. This has been shown to result in high false positive rates.

Pitfalls in the statistical analysis of microbiome amplicon sequencing data.

Microbiome data are characterized by several aspects that make them challenging to analyse statistically: they are compositional, high dimensional and rich in zeros. A large array of statistical methods exist to analyse these data. Some are borrowed from other fields, such as ecology or RNA-sequencing, while others are custom-made for microbiome data.

Using random forest to identify longitudinal predictors of health in a 30-year cohort study.

Due to the wealth of exposome data from longitudinal cohort studies that is currently available, the need for methods to adequately analyze these data is growing. We propose an approach in which machine learning is used to identify longitudinal exposome-related predictors of health, and illustrate its potential through an application. Our application involves studying the relation between exposome and self-perceived health based on the 30-year running Doetinchem Cohort Study.

Early environmental quality and life-course mental health effects: The Equal-Life project.

Background: There is increasing evidence that a complex interplay of factors within environments in which children grows up, contributes to children's suboptimal mental health and cognitive development. The concept of the life-course exposome helps to study the impact of the physical and social environment, including social inequities, on cognitive development and mental health over time.

Methods: Equal-Life develops and tests combined exposures and their effects on children's mental health and cognitive development.

Low Meat Consumption in the Netherlands Is Associated With Higher Intake of Fish, Nuts, Seeds, Cheese, Sweets, and Snacks: Results From a Two-Part Model.

Studies on sustainable diets show a need for replacement of animal-based foods by plant-based foods, which is also called "the protein transition." To gain insight into the acceptability of such diet shifts, this study evaluated which current food sources people consume at varying amounts of meat consumption. The study population consisted of 4,313 participants aged 1-79 years of the Dutch National Food Consumption Survey 2012-2016, which assessed diet using two nonconsecutive 24-h dietary recalls.

Diverging metabolic effects of 2 energy-restricted diets differing in nutrient quality: a 12-week randomized controlled trial in subjects with abdominal obesity.

Background: Despite the established relation between energy restriction (ER) and metabolic health, the most beneficial nutrient composition of a weight-loss diet is still a subject of debate.

Objectives: The aim of the study was to examine the additional effects of nutrient quality on top of ER.

Methods: A parallel-designed, 12-week 25% ER dietary intervention study was conducted (clinicaltrials.

The mediating role of unhealthy behavior in the relationship between shift work and perceived health.

Background: Little is known about the relationship between shift work and perceived health, including potential underlying mechanisms such as unhealthy behaviors. The aim of this study was to investigate whether unhealthy behaviors mediate the relationship between shift work and perceived mental and physical health, taking into account potential differences by level of education.

Methods: Data from 1633 workers participating in the Doetinchem Cohort Study during 1995-2016 were used.

Mapping chronic disease prevalence based on medication use and socio-demographic variables: an application of LASSO on administrative data sources in healthcare in the Netherlands.

Background: Policymakers generally lack sufficiently detailed health information to develop localized health policy plans. Chronic disease prevalence mapping is difficult as accurate direct sources are often lacking. Improvement is possible by adding extra information such as medication use and demographic information to identify disease.

Identification of Lifestyle Behaviors Associated with Recurrence and Survival in Colorectal Cancer Patients Using Random Survival Forests.

Current lifestyle recommendations for cancer survivors are the same as those for the general public to decrease their risk of cancer. However, it is unclear which lifestyle behaviors are most important for prognosis. We aimed to identify which lifestyle behaviors were most important regarding colorectal cancer (CRC) recurrence and all-cause mortality with a data-driven method.

A Systematic Review and Meta-Analysis of Validation Studies Performed on Dietary Record Apps.

Mobile dietary record apps have been increasingly validated by studies with various study designs. This review aims to evaluate the overall accuracy of dietary record apps in measuring the intake of energy, macro- and micronutrients, and food groups in real-life settings and the designs of validation studies. We systematically searched mobile dietary record validation studies published during the period from 2013 to 2019.