👤 Yannis Manios

Health apps designed to monitor, motivate, and educate people towards their health goals are getting more users and features each time. These apps offer valuable support for self-managing health behaviors and achieving long-term objectives. However, there is limited understanding of user preferences regarding essential app features. The aim of the study is to get insights about potential users' preferences, in order to tailor better apps for lifestyle management. We conducted a three-part web survey with 389 respondents from four countries as part of the DigiCare4You European Union (EU) project. In the first part, we collected the socioeconomic characteristics and health status of each respondent. In the following stage, we asked five questions on a Likert scale to ascertain the individual level of usage and general attitude towards technology. Finally, we performed a discrete choice experiment (DCE) using an unlabeled design and estimated the odds ratio for each feature using conditional logit analysis. We also ran alternative estimations stratifying by non-communicable disease (NCD) patients and non-NCD patients, and explored latent profile analysis (LPA) to understand whether the general attitude towards technology impacts the preference pattern between users. The DCE revealed that respondents showed a clear preference for monitoring physical health over emotional status. They favored receiving lifestyle achievement notifications weekly rather than daily, and daily rather than more frequently. Similarly, respondents preferred uploading body weight measurements on a weekly or monthly basis rather than daily. Users expressed a preference for collaborating with their doctors to set exercise and diet goals, rather than either deciding independently or delegating entirely to their doctors. End-users also show a pattern of preferring notifications for goals instead of challenging other users. Preferences regarding the subjects of health content between workout routines, food recipes, and new scientific evidence were not significant; also, no statistical significance was found for the decision between follow-up visits with their doctor in person or remotely. LPA returned two groups regarding their general attitude towards technology: a lower, an intermediate, and a higher usage in their private life based on their responses to the questionnaire. Stratified DCEs have shown heterogeneity of users' preferences according to their specific attitude towards technology. Our study indicates that potential mobile health (mHealth) app users managing chronic conditions prefer platforms that enable shared responsibility with their doctors in defining health goals while having an intermediate level of interaction frequency with the app. These findings are key to tailoring mHealth apps that can optimize motivation triggers, support healthier lifestyles, and empower patients with chronic conditions. Show less

A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. We used mathematical modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Among other food items, fish, pizza, chicken, and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. Selecting food items using multiple hypothesis testing is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set. Show less

Recent genome-wide association studies have identified a single nucleotide polymorphism within the last intron of MAP2K5 associated with a higher body mass index (BMI) in adults. MAP2K5 is a component of the MAPK-family intracellular signaling pathways, responding to extracellular growth factors such as brain derived neurotrophic factor (BDNF) and nerve growth factor (NGF). In this study, we examined the association of this variant in two cohorts of children from Sweden and Greece. We examine the association of rs2241423 to BMI in a cohort of 474 Swedish children admitted for treatment of childhood obesity and 519 children matched for gender, ethnicity and socioeconomic background from the Stockholm area, as well as a cross-sectional cohort of 2308 Greek school children (Healthy Growth Study). Children were genotyped using a predesigned TaqMan polymorphism assay. Logistic regression was used to test for an association of rs2241423 to obesity in the cohort of Swedish children. Linear regression was used to test for an association of rs2241423 to BMI z-score and phenotypic measurements of body adiposity in the cohort of Greek children. Models were adjusted for age and gender. In the cohort of Greek children the model was also adjusted for stage of pubertal development. The minor allele of rs2241423, allele A, was associated with a protective effect against obesity in the cohort of Swedish children (p = 0.029, OR = 0.79 (95% CI: 0.64-0.98)), and with a lower BMI z-score in the cohort of Greek children (p = 0.028, β = -0.092). No association to phenotypic measurements of body fat distribution could be observed in our study. rs2241423 was associated with BMI and obesity in two independent European cohorts suggesting a role for MAP2K5 in early weight regulation. Show less